You searched for +publisher:"University of New Mexico" +contributor:("Moses, Melanie").
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University of New Mexico
1.
Miles, Edward C.
Hopscotch: Robust Multi-agent Search.
Degree: Department of Computer Science, 2013, University of New Mexico
URL: http://hdl.handle.net/1928/23202 
► The task of searching a space is critical to a wide range of diverse applications such as land mine clearing and planetary exploration. Because applications…
(more)
▼ The task of searching a space is critical to a wide range of diverse applications such as land mine clearing and planetary exploration. Because applications frequently require searching remote or hazardous locations, and because the task is easily divisible, it is natural to consider the use of multi-robot teams to accomplish the search task. An important topic of research in this area is the division of the task among robot agents. Interrelated with subtask assignment is failure handling, in the sense that, when an agent fails, its part of the task must then be performed by other agents. This thesis describes Hopscotch, a multi-agent search strategy that divides the search area into a grid of lots. Each agent is assigned responsibility to search one lot at a time, and upon completing the search of that lot the agent is assigned a
new lot. Assignment occurs in real time using a simple contract net. Because lots that have been previously searched are skipped, the order of search from the point of view of a particular agent is reminiscent of the progression of steps in the playground game of Hopscotch. Decomposition of the search area is a common approach to multi-agent search, and auction-based contract net strategies have appeared in recent literature as a method of task allocation in multi-agent systems. The Hopscotch strategy combines the two, with a strong focus on robust tolerance of agent failures. Contract nets typically divide all known tasks among available resources. In contrast, Hopscotch limits each agent to one assigned lot at a time, so that failure of an agent compels re-allocation of only one lot search task. Furthermore, the contract net is implemented in an unconventional manner that empowers each agent with responsibility for contract management. This novel combination of real-time assignment and decentralized management allows Hopscotch to resiliently cope with agent failures. The Hopscotch strategy was modeled and compared to other multi-agent strate- gies that tackle the search task in a variety of ways. Simulation results show that Hopscotch is failure-tolerant and very effective in comparison to the other approaches in terms of both search time and search efficiency. Although the search task modeled here is a basic one, results from simulations show the promise of using this strategy for more complicated scenarios, and with actual robot agents.
Advisors/Committee Members: Moses, Melanie E., Moses, Melanie E., Tapia, Lydia, Fierro, Rafael.
Subjects/Keywords: multi-agent; search; coverage; task allocation; mobile robots; cellular decomposition; contract net; swarm robotics
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APA (6th Edition):
Miles, E. C. (2013). Hopscotch: Robust Multi-agent Search. (Masters Thesis). University of New Mexico. Retrieved from http://hdl.handle.net/1928/23202
Chicago Manual of Style (16th Edition):
Miles, Edward C. “Hopscotch: Robust Multi-agent Search.” 2013. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/23202.
MLA Handbook (7th Edition):
Miles, Edward C. “Hopscotch: Robust Multi-agent Search.” 2013. Web. 18 Jul 2019.
Vancouver:
Miles EC. Hopscotch: Robust Multi-agent Search. [Internet] [Masters thesis]. University of New Mexico; 2013. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/23202.
Council of Science Editors:
Miles EC. Hopscotch: Robust Multi-agent Search. [Masters Thesis]. University of New Mexico; 2013. Available from: http://hdl.handle.net/1928/23202
University of New Mexico
2.
Bezzo, Nicola.
Coordination strategies for connected robotic networks.
Degree: Electrical and Computer Engineering, 2013, University of New Mexico
URL: http://hdl.handle.net/1928/22030
► In this dissertation we present theoretical techniques to coordinate multi-robotic systems in cluttered environment considering sensing, manipulation, and communication constraints. We address communication constraints in…
(more)
▼ In this dissertation we present theoretical techniques to coordinate multi-robotic systems in cluttered environment considering sensing, manipulation, and communication constraints. We address communication constraints in the context of mobile routers coordination within complex operations. Motivated by real world applications, we present strategies to deploy teams of robotic agents with communication connectivity constraints to keep a user connected to a base station at all times. We consider several aspects about wireless communication to improve the connection quality of mobile robotic systems while performing cooperative missions inspired by real world applications. This dissertation is organized in two main parts. In Part I we study networks of homogeneous robots consisting of agents having the same dynamics, sensing, and communication capabilities. We first present a centralized approach based on disjunctive programming to tether a chain of mobile routers between a base station and a user that is moving in a concave environment. We consider line-of-sight (LOS) communication and use a mixed integer approach to determine the number of required agents and their goal locations. Because centralized approaches have the limitation that a central node has to compute all the operations and everything has to be known a priori, we study decentralized approaches to swarm groups of mobile agents while considering communication constraints. Specifically we introduce a spring-mass virtual interaction between the agents and use artificial potentials to navigate the network in a cluttered environment. Finally we use bit error rate (BER) optimization to maintain a certain quality of communication while keeping the system stable in the sense of Lyapunov. When dealing with connected networks of mobile robots, the problem of detecting variations in the topology is an important area of study. Therefore we present a novel decentralized technique to detect and estimate changes in the topology of mobile robotic networks. In this case we assume that each robot is equipped with a chaotic oscillator whose state is propagated to the other robots through wireless communication. The key idea of our approach is that every node receives an aggregate signal from the surrounding neighbors, which can be used to detect changes in the local network topology. We introduce an adaptive strategy that each robot independently implements to: (i) estimate the net coupling of all the oscillators in its neighborhood, and (ii) synchronize the state of the oscillators onto the same time evolution. We show that by using this strategy, synchronization can be attained and changes of the network topology can be detected. Finally in the last chapter of Part I we exploit antenna diversity in a practical case study to localize and improve the signal quality between a mobile agent and a user. In Part II we focus our attention on heterogeneous systems. With the term heterogeneous we imply the synergy of multiple robotic platforms characterized by different dynamics…
Advisors/Committee Members: Fierro, Rafael, Abdallah, Chaouki T., Sorrentino, Francesco, Moses, Melanie.
Subjects/Keywords: Robots – Control systems.; Multiagent systems.; Swarm intelligence.; Bit error rate.; Local area networks (Computer networks); Local area networks (Computer networks); Heterogeneous computing.
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APA (6th Edition):
Bezzo, N. (2013). Coordination strategies for connected robotic networks. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/22030
Chicago Manual of Style (16th Edition):
Bezzo, Nicola. “Coordination strategies for connected robotic networks.” 2013. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/22030.
MLA Handbook (7th Edition):
Bezzo, Nicola. “Coordination strategies for connected robotic networks.” 2013. Web. 18 Jul 2019.
Vancouver:
Bezzo N. Coordination strategies for connected robotic networks. [Internet] [Doctoral dissertation]. University of New Mexico; 2013. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/22030.
Council of Science Editors:
Bezzo N. Coordination strategies for connected robotic networks. [Doctoral Dissertation]. University of New Mexico; 2013. Available from: http://hdl.handle.net/1928/22030
University of New Mexico
3.
Ericksen, John.
Transfuse: A Compile-Time Metaprogramming Solution for Reducing Boilerplate on Google's Android.
Degree: Department of Computer Science, 2016, University of New Mexico
URL: http://hdl.handle.net/1928/32945
► Modern Java application development makes use of metaprogramming to offset and reduce application boilerplate. Unfortunately, metaprogramming techniques typically require a relatively high run-time cost, particularly…
(more)
▼ Modern Java application development makes use of metaprogramming to offset and reduce application boilerplate.
Unfortunately, metaprogramming techniques typically require a relatively high run-time cost, particularly at application startup.
Therefore, environments with limited resources or without the luxury of a warm-up period, often lack metaprogramming as an option.
This is precisely the case with applications written for Google Android.
Android applications run on low resource mobile hardware and lack an offline startup period.
Therefore, Android applications often suffer from a high amount of boilerplate.
Fortunately, there is an alternative to the traditional metaprogramming approach.
In this thesis, we examine the approach of a metaprogramming tool named Transfuse.
Transfuse targets boilerplate reduction within the constraints prescribed by the Android environment.
This is accomplished through compile-time analysis and code generation.
This approach is analyzed from both boilerplate reduction and run-time performance perspectives.
Advisors/Committee Members: Stefanovic, Darko, Moses, Melanie, Kelly, Patrick.
Subjects/Keywords: Dependency Injection; Android; Compile time; Annotation Processing; Metaprogramming; Boilerplate
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APA (6th Edition):
Ericksen, J. (2016). Transfuse: A Compile-Time Metaprogramming Solution for Reducing Boilerplate on Google's Android. (Masters Thesis). University of New Mexico. Retrieved from http://hdl.handle.net/1928/32945
Chicago Manual of Style (16th Edition):
Ericksen, John. “Transfuse: A Compile-Time Metaprogramming Solution for Reducing Boilerplate on Google's Android.” 2016. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/32945.
MLA Handbook (7th Edition):
Ericksen, John. “Transfuse: A Compile-Time Metaprogramming Solution for Reducing Boilerplate on Google's Android.” 2016. Web. 18 Jul 2019.
Vancouver:
Ericksen J. Transfuse: A Compile-Time Metaprogramming Solution for Reducing Boilerplate on Google's Android. [Internet] [Masters thesis]. University of New Mexico; 2016. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/32945.
Council of Science Editors:
Ericksen J. Transfuse: A Compile-Time Metaprogramming Solution for Reducing Boilerplate on Google's Android. [Masters Thesis]. University of New Mexico; 2016. Available from: http://hdl.handle.net/1928/32945
University of New Mexico
4.
Schulte, Eric.
Neutral Networks of Real-World Programs and their Application to Automated Software Evolution.
Degree: Department of Computer Science, 2014, University of New Mexico
URL: http://hdl.handle.net/1928/25819
► The existing software development ecosystem is the product of evolutionary forces, and consequently real-world software is amenable to improvement through automated evolutionary techniques. This dissertation…
(more)
▼ The existing software development ecosystem is the product of evolutionary forces, and consequently real-world software is amenable to improvement through automated evolutionary techniques. This dissertation presents empirical evidence that software is inherently robust to small randomized program transformations, or 'mutations. Simple and general mutation operations are demonstrated that can be applied to software source code, compiled assembler code, or directly to binary executables. These mutations often generate variants of working programs that differ significantly from the original, yet remain fully functional. Applying successive mutations to the same software program uncovers large 'neutral networks' of fully functional variants of real-world software projects. These properties of 'mutational robustness' and the corresponding 'neutral networks' have been studied extensively in biology and are believed to be related to the capacity for unsupervised evolution and adaptation. As in biological systems, mutational robustness and neutral networks in software systems enable automated evolution. The dissertation presents several applications that leverage software neutral networks to automate common software development and maintenance tasks. Neutral networks are explored to generate diverse implementations of software for improving runtime security and for proactively repairing latent bugs. Next, a technique is introduced for automatically repairing bugs in the assembler and executables compiled from off-the-shelf software. As demonstration, a proprietary executable is manipulated to patch security vulnerabilities without access to source code or any aid from the software vendor. Finally, software neutral networks are leveraged to optimize complex nonfunctional runtime properties. This optimization technique is used to reduce the energy consumption of the popular PARSEC benchmark applications by 20% as compared to the best available public domain compiler optimizations. The applications presented herein apply evolutionary computation techniques to existing software using common software engineering tools. By enabling evolutionary techniques within the existing software development toolchain, this work is more likely to be of practical benefit to the developers and maintainers of real-world software systems.
Advisors/Committee Members: Forrest, Stephanie, Weimer, Westley, Crandall, Jedidiah, Moses, Melanie.
Subjects/Keywords: software engineering; search based software engineering; software mutational robustness; mutational robustness; evolutionary computation; genetic algorithm; genetic programming; optimization; automated program repair; automated software engineering; bug repair; fitness landscape; instruction set architecture; neutral network
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APA (6th Edition):
Schulte, E. (2014). Neutral Networks of Real-World Programs and their Application to Automated Software Evolution. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/25819
Chicago Manual of Style (16th Edition):
Schulte, Eric. “Neutral Networks of Real-World Programs and their Application to Automated Software Evolution.” 2014. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/25819.
MLA Handbook (7th Edition):
Schulte, Eric. “Neutral Networks of Real-World Programs and their Application to Automated Software Evolution.” 2014. Web. 18 Jul 2019.
Vancouver:
Schulte E. Neutral Networks of Real-World Programs and their Application to Automated Software Evolution. [Internet] [Doctoral dissertation]. University of New Mexico; 2014. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/25819.
Council of Science Editors:
Schulte E. Neutral Networks of Real-World Programs and their Application to Automated Software Evolution. [Doctoral Dissertation]. University of New Mexico; 2014. Available from: http://hdl.handle.net/1928/25819
University of New Mexico
5.
Chang, Michael.
Scaling of crop diversity and optimal allocation of foodshed infrastructure.
Degree: UNM Biology Department, 2013, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/14
► Food hubs are organizations that manage the aggregation and distribution of local products, and are a small, but growing means to satisfy high demand…
(more)
▼ Food hubs are organizations that manage the aggregation and distribution of local products, and are a small, but growing means to satisfy high demand for diverse, healthy diets. However, economic barriers inhibit small producers and distributors from developing mainstream, local consumer alternatives to industrial-scale products. To build foodshed, distribution hubs could help overcome these challenges by reducing costs through shared refrigeration, processing, and transportation infrastructure. However, there is no theory to help plan them. I present and test theory to allocate foodshed infrastructure based on insight by Dunn, et al. (2011) that Shannon diversity measured relative to a whole set of sites, rather than site-by-site, reveals law-like scaling behavior. I accessed the US Dept of Agricultures 2011 Cropland Data Layer (CDL) for 40 crop cover types at 30 m resolution in
New Mexico. I tested two competing hypotheses: 1) a site-specific and 2) a whole-system normalization of crop probabilities interpretable as the information experienced by producers versus a distributor, respectively. Directly edible and marketable crops were differentiated from forage crops for livestock because of the different destinations and infrastructure they require. A distributor with information about the whole foodshed experiences law-like increase in uncertainty with increasing observation scales. Since the distributor uncertainty about an area's crop inventory is an order of magnitude lower than the producers', a distributor should plan infrastructure at a scale that maximizes reduction of a producer's uncertainty. For all crops, I compared their relative contribution to total diversity per unit area so as to compare areas on the landscape with the highest capacity to diversify the foodshed as a whole. Development of a diverse foodshed will require knowledge of which products affect local diversity. This work grounds whole-foodshed planning in ecological theory, and contributes to understanding about how the conventional food system has allocated crop diversity.
Advisors/Committee Members: Milne, Bruce, Moses, Melanie, Duvall, Chris, N/A.
Subjects/Keywords: Food; Agriculture; Sustainability; Diversity; Entropy; Cropland Data Layer; Hierarchy; Agrobiodiversity – Economic aspects.; Sustainable agriculture – Planning.; Farms; Small – Management.; Food supply – Social aspects.; Farmers' markets – Planning.; Local foods.; Biology
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APA (6th Edition):
Chang, M. (2013). Scaling of crop diversity and optimal allocation of foodshed infrastructure. (Masters Thesis). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/14
Chicago Manual of Style (16th Edition):
Chang, Michael. “Scaling of crop diversity and optimal allocation of foodshed infrastructure.” 2013. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/14.
MLA Handbook (7th Edition):
Chang, Michael. “Scaling of crop diversity and optimal allocation of foodshed infrastructure.” 2013. Web. 18 Jul 2019.
Vancouver:
Chang M. Scaling of crop diversity and optimal allocation of foodshed infrastructure. [Internet] [Masters thesis]. University of New Mexico; 2013. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/14.
Council of Science Editors:
Chang M. Scaling of crop diversity and optimal allocation of foodshed infrastructure. [Masters Thesis]. University of New Mexico; 2013. Available from: https://digitalrepository.unm.edu/biol_etds/14
University of New Mexico
6.
Brunetti, Tonya.
Transcriptional regulation of muscle development in Drosophila melanogaster.
Degree: UNM Biology Department, 2015, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/9
► The transcriptional regulation of muscle development involves several complex processes that must work together in order to form functional, syncytial muscle cells. However, when transcription…
(more)
▼ The transcriptional regulation of muscle development involves several complex processes that must work together in order to form functional, syncytial muscle cells. However, when transcription is mis-regulated, muscle development is often times negatively affected and can lead to muscle diseases such as muscular dystrophy and cardiac myopathies. In order to gain more insight into how transcription is regulated, I use Drosophila melanogaster as a model for understanding muscle development. In chapter one, I use a traditional genetic screen to phenotypically and molecularly identify two Hox co-factors, extradenticle and homothorax, that have the ability to change muscle identity. Additionally, in chapter two, through the identification of a mechanism, I identify a gene critical in adult myoblast fusion and is directly regulated by the transcription factor, Myocyte Enhancer Factor-2 (MEF2). Lastly, in chapter three a computation approach is used to discover
new potential co-factor binding sites that may work in conjunction with MEF2 in transcriptional muscle regulation. Together, these results provide
new information into how muscle is transcriptionally regulated during different stages of development.
Advisors/Committee Members: Cripps, Richard, Stricker, Stephen, Johnston, Christopher, Moses, Melanie.
Subjects/Keywords: Drosophila melanogaster; muscle development; genetic algorithm; myocyte enhancer factor-2; myoblast fusion; entropy; transcriptional regulation
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APA (6th Edition):
Brunetti, T. (2015). Transcriptional regulation of muscle development in Drosophila melanogaster. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/9
Chicago Manual of Style (16th Edition):
Brunetti, Tonya. “Transcriptional regulation of muscle development in Drosophila melanogaster.” 2015. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/9.
MLA Handbook (7th Edition):
Brunetti, Tonya. “Transcriptional regulation of muscle development in Drosophila melanogaster.” 2015. Web. 18 Jul 2019.
Vancouver:
Brunetti T. Transcriptional regulation of muscle development in Drosophila melanogaster. [Internet] [Doctoral dissertation]. University of New Mexico; 2015. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/9.
Council of Science Editors:
Brunetti T. Transcriptional regulation of muscle development in Drosophila melanogaster. [Doctoral Dissertation]. University of New Mexico; 2015. Available from: https://digitalrepository.unm.edu/biol_etds/9
University of New Mexico
7.
Burger, Joseph Robert.
Macroecology and Sociobiology of Humans and other Mammals.
Degree: UNM Biology Department, 2015, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/11
► Despite being the most studied species on the planet, ecologists typically do not study humans the same way we study other organisms. My Ph.D. thesis…
(more)
▼ Despite being the most studied species on the planet, ecologists typically do not study humans the same way we study other organisms. My Ph.D. thesis contributes to scientific development in two ways: i) synthesizing our understand of the inter and intraspecific variation in social behavior in an understudied rodent lineage, the caviomorphs, providing a comparative context to understand social evolution in general, and 2) developing a macroecological approach to understand the metabolic trajectory of the human species. Through comparative analysis, chapter 2 synthesizes the available information on the diversity of sociality in the caviomorph rodents, both within and across species. Studies and theory derived from better-studied mammalian taxa establish an integrative and comparative framework from which to examine social systems in caviomorphs. We synthesize the literature to evaluate variation in space use, group size, mating systems, and parental care strategies in caviomorphs in the context of current hypotheses. We highlight unique aspects of caviomorph biology and offer potentially fruitful lines for future research both at the inter and intraspecific levels. We can gain unique insights into the ecological drivers and evolutionary significance of diverse animal societies by studying this diverse taxon. Chapter 3 outlines core ecological principles that should be integral to a science of sustainability: 1) physical conservation laws govern the flows of energy and materials between human systems and the environment, 2) smaller systems are connected by these flows to larger systems in which they are embedded, 3) global constraints ultimately limit flows at smaller scales. Over the past few decades, decreasing per-capita rates of consumption of petroleum, phosphate, agricultural land, fresh water, fish, and wood indicate that the growing human population has surpassed the capacity of the Earth to supply enough of these essential resources to sustain even the current population and level of socioeconomic development. Chapter 4 applies a socio-metabolic perspective of the urban transition coupled with empirical examination of cross-country data spanning decades. It highlights the central role of extra-metabolic energy in global urbanization and the coinciding transition from resource extraction to industrial and service economies. The global urban transition from resource producers in rural areas, to industrial and service employment in urban systems is fuelled by supplementing extra-metabolic energy in the form of fossil fuels for decreasing human and animal labor. Collectively, I hope this work demonstrates the utility of comparative analysis and synthesis in understanding the evolutionary ecology of sociality and the power of a macroecological approach in understanding the metabolic ecology and trajectory of the human species.
Advisors/Committee Members: Brown, James, Smith, Felisa, Moses, Melanie, Milne, Bruce.
Subjects/Keywords: Human Ecology; Macroecology; Metabolic Ecology; Sociality; Sustainability; Cities
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APA ·
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Manager
APA (6th Edition):
Burger, J. R. (2015). Macroecology and Sociobiology of Humans and other Mammals. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/11
Chicago Manual of Style (16th Edition):
Burger, Joseph Robert. “Macroecology and Sociobiology of Humans and other Mammals.” 2015. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/11.
MLA Handbook (7th Edition):
Burger, Joseph Robert. “Macroecology and Sociobiology of Humans and other Mammals.” 2015. Web. 18 Jul 2019.
Vancouver:
Burger JR. Macroecology and Sociobiology of Humans and other Mammals. [Internet] [Doctoral dissertation]. University of New Mexico; 2015. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/11.
Council of Science Editors:
Burger JR. Macroecology and Sociobiology of Humans and other Mammals. [Doctoral Dissertation]. University of New Mexico; 2015. Available from: https://digitalrepository.unm.edu/biol_etds/11
University of New Mexico
8.
Burnside, William.
Pattern and process in metabolic ecology : from biotic interactions to cultural diversity gradients.
Degree: UNM Biology Department, 2012, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/12
► Many ecological patterns and processes are functions of metabolism (Brown 2004), meaning the acquisition, transformation, and allocation of energy, materials, and information within the bodies…
(more)
▼ Many ecological patterns and processes are functions of metabolism (Brown 2004), meaning the acquisition, transformation, and allocation of energy, materials, and information within the bodies of individuals and among members of human and other animal societies. Individual metabolic rate should influence behavior by determining the energy available for action as well as the rate at which the body requires fuel. First, I test a key prediction of the metabolic theory of ecology (MTE), that biotic interaction rates are characteristic functions of temperature. Findings support this prediction and suggest that herbivory, predation, parasitism, parasitoidy, and competition increase exponentially with temperature and that this increase echoes that of individual metabolic rates. Second, I extend a metabolic framework to foraging patterns and space use of traditional human societies. Together with colleagues, I build on Hamilton (2007) to offer a model that formally incorporates hypothesized mechanisms affecting population sizes and densities and territory sizes: temperature, productivity, seasonality, and trophic level (degree of carnivory). We test this model on a dataset of 333 traditional foraging societies using multiple linear regression. Interactions between explanatory variables were important, and the influence of temperature, productivity, and seasonality often depended on trophic level. In addition, coastal productivity allowed marine foragers to disassociate themselves from terrestrial energetic constraints and maintain high population densities, small territory sizes, and thus high levels of cultural diversity. A metabolic perspective is useful for interpreting patterns in large scale human ecology and suggesting underlying mechanisms. Third, I argue for a macroecological approach to human ecology and suggest the value of a metabolic perspective using examples from human foraging ecology, life history, space use, population structure, disease ecology, cultural and linguistic diversity patterns, and industrial and urban systems. The ability of a metabolic framework to inform our understanding of behavior, from the interaction rates of small ectotherms to cultural diversity and urban activity patterns in Homo sapiens, suggests the power and promise of this approach.
Advisors/Committee Members: Brown, James, Moses, Melanie, Kaplan, Hillard, Hamilton, Marcus.
Subjects/Keywords: metabolic ecology macroecology
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APA (6th Edition):
Burnside, W. (2012). Pattern and process in metabolic ecology : from biotic interactions to cultural diversity gradients. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/12
Chicago Manual of Style (16th Edition):
Burnside, William. “Pattern and process in metabolic ecology : from biotic interactions to cultural diversity gradients.” 2012. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/12.
MLA Handbook (7th Edition):
Burnside, William. “Pattern and process in metabolic ecology : from biotic interactions to cultural diversity gradients.” 2012. Web. 18 Jul 2019.
Vancouver:
Burnside W. Pattern and process in metabolic ecology : from biotic interactions to cultural diversity gradients. [Internet] [Doctoral dissertation]. University of New Mexico; 2012. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/12.
Council of Science Editors:
Burnside W. Pattern and process in metabolic ecology : from biotic interactions to cultural diversity gradients. [Doctoral Dissertation]. University of New Mexico; 2012. Available from: https://digitalrepository.unm.edu/biol_etds/12
University of New Mexico
9.
Okie, Jordan G.
Allometric scaling and metabolic ecology of microorganisms and major evolutionary transitions.
Degree: UNM Biology Department, 2011, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/89
► My dissertation centers around investigating big-picture questions related to understanding the consequences of metabolism and energetics on the evolution, ecology, and physiology of life. The…
(more)
▼ My dissertation centers around investigating big-picture questions related to understanding the consequences of metabolism and energetics on the evolution, ecology, and physiology of life. The evolutionary transitions from prokaryotes to unicellular eukaryotes to multicellular organisms were accompanied by major innovations in metabolic design. In my first chapter, I show that the scaling of metabolic rate, population growth rate, and production efficiency with body size have changed across these transitions. Metabolic rate scales with body mass superlinearly in prokaryotes, linearly in protists, and sublinearly in metazoans, so Kleibers 3/4 power scaling law does not apply universally across organisms. This means that major changes in metabolic processes during the early evolution of life overcame existing physical constraints, exploited
new opportunities, and imposed
new constraints on organism physiology. Surface areas of physiological structures of organisms impose fundamental constraints on metabolic rate. In my second chapter, I demonstrate that organisms have a variety of options for increasing the scaling of the area of their metabolic surfaces with body sizes. I develop models and examples illustrating the role of cell membrane elaborations, mitochondria, vacuoles, vesicles, inclusions, and shape-shifting in the architectural design, evolution, and ecology of unicellular microbes. I demonstrate how these surface-area scaling adaptations have played important roles in the evolution of major biological designs of cells and the physiological ecology of organisms. In my third and final chapter, I integrate and synthesize findings from the previous two chapters with important developments in geochemistry, microbiology, and astrobiology in order to identify the fundamental physical and biological dimensions that characterize a metabolic theory of ecology of microorganisms. These dimensions are thermodynamics, chemical kinetics, physiological harshness, cell size, and levels of biological organization. I show how addressing these dimensions can inform understanding of the physical and biological factors governing the metabolic rate, growth rate, and geographic distribution of cells. I propose a unifying theory to understand how the major ecological and evolutionary transitions that led to increases in levels of organization of life, such as endosymbiosis, multicellularity, eusociality, and multi-domain complexes, influences the metabolism and growth and the metabolic scaling of these complexes.
Advisors/Committee Members: Brown, James H., Michod, Richard, Moses, Melanie, Sinsabaugh, Robert.
Subjects/Keywords: Major evolutionary transitions; Metabolic theory of ecology; Microbial ecology; Thermodynamics; Kinetics; Allometric scaling; Unicellular organisms; Body size; Cell physiological ecology
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APA (6th Edition):
Okie, J. G. (2011). Allometric scaling and metabolic ecology of microorganisms and major evolutionary transitions. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/89
Chicago Manual of Style (16th Edition):
Okie, Jordan G. “Allometric scaling and metabolic ecology of microorganisms and major evolutionary transitions.” 2011. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/89.
MLA Handbook (7th Edition):
Okie, Jordan G. “Allometric scaling and metabolic ecology of microorganisms and major evolutionary transitions.” 2011. Web. 18 Jul 2019.
Vancouver:
Okie JG. Allometric scaling and metabolic ecology of microorganisms and major evolutionary transitions. [Internet] [Doctoral dissertation]. University of New Mexico; 2011. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/89.
Council of Science Editors:
Okie JG. Allometric scaling and metabolic ecology of microorganisms and major evolutionary transitions. [Doctoral Dissertation]. University of New Mexico; 2011. Available from: https://digitalrepository.unm.edu/biol_etds/89
University of New Mexico
10.
Scholle, Stacy O'Neil.
Temporal dynamics and spatial analysis of competing dengue 2 virus strains in the Americas.
Degree: UNM Biology Department, 2010, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/90
► The dengue virus is the causative agent of an important re-emerging infectious disease that has become increasingly significant in tropical America and the Caribbean…
(more)
▼ The dengue virus is the causative agent of an important re-emerging infectious disease that has become increasingly significant in tropical America and the Caribbean due to the infiltration of a more pathogenic Asian/American strain of dengue serotype 2 into the population. This invading strain is responsible for epidemics of dengue hemorrhagic fever, a life-threatening disease that was not previously a large public health concern in the region. Here, I create a historical map of the invasion and replacement of the endemic American strain of dengue 2 by the Asian/American strain, showing that the timing of invasion spans 25 years, and is highly variable in the region. In addition, I model the competitive dynamics of the two strains using differential equa- tion models. By calculating and comparing the basic reproductive ratio (R0) for the Asian/American and American strain of dengue 2, I identify potential evolutionary trade-offs between the two strains and the ecological circumstances that benefit one trade-off over another. Numerically solving my models help to understand possible mechanisms behind variable timing of invasion by the Asian/American strain. The fitness gain resulting from the Asian/American strains shorter latency period increases as the adult vector mortality rate increases, indicating that regions where adult mosquito death rate is high will select for the more virulent strain of dengue 2.
Advisors/Committee Members: Wearing, Helen, Moses, Melanie, Witt, Christopher.
Subjects/Keywords: Dengue; Biology; Biology
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APA (6th Edition):
Scholle, S. O. (2010). Temporal dynamics and spatial analysis of competing dengue 2 virus strains in the Americas. (Masters Thesis). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/90
Chicago Manual of Style (16th Edition):
Scholle, Stacy O'Neil. “Temporal dynamics and spatial analysis of competing dengue 2 virus strains in the Americas.” 2010. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/90.
MLA Handbook (7th Edition):
Scholle, Stacy O'Neil. “Temporal dynamics and spatial analysis of competing dengue 2 virus strains in the Americas.” 2010. Web. 18 Jul 2019.
Vancouver:
Scholle SO. Temporal dynamics and spatial analysis of competing dengue 2 virus strains in the Americas. [Internet] [Masters thesis]. University of New Mexico; 2010. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/90.
Council of Science Editors:
Scholle SO. Temporal dynamics and spatial analysis of competing dengue 2 virus strains in the Americas. [Masters Thesis]. University of New Mexico; 2010. Available from: https://digitalrepository.unm.edu/biol_etds/90
University of New Mexico
11.
Flanagan, Tatiana.
How ants turn information into food.
Degree: UNM Biology Department, 2015, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/37
► Animals constantly process information from their environment. In social organisms, information exchange among individuals allows for behaviors to be finely tuned to local environmental cues.…
(more)
▼ Animals constantly process information from their environment. In social organisms, information exchange among individuals allows for behaviors to be finely tuned to local environmental cues. Such is the case of foraging in ants, where sharing information about the distribution of resources can drive adaptive behaviors to exploit those resources. In a first study, we quantified how clustering of experimental seed baits significantly increased foraging rates of seed harvester ants. That study found that species with larger colonies were no better than species with smaller colonies at collecting clumped seeds. In a second study, we integrated computer simulations, information science and computational analysis to re-analyze data. We found that seed intake patterns from larger colonies were more consistent with foraging patterns generated by behaviors that use information, such as recruitment and site fidelity, particularly for foraging on clustered distributions of resources. Finally, we studied recruitment behavior in large colonies of Argentine ants. Our results indicate that Argentine ants recruit nestmates to food directly from persistent nearby trails. Once ants find a
new food source, they walk back and forth between the bait and sometimes share food by trophallaxis with nestmates on the trail. Recruiting ants from nearby persistent trails creates a dynamic circuit, like those found in other distributed systems, which facilitates a quick response to changes in available resources. These studies quantify how remembering and communicating information in a range of colony sizes increase foraging rates.
Advisors/Committee Members: Moses, Melanie, Brown, James, Wearing, Helen, Gordon, Deborah.
Subjects/Keywords: ant foraging; information; colony size
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APA (6th Edition):
Flanagan, T. (2015). How ants turn information into food. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/37
Chicago Manual of Style (16th Edition):
Flanagan, Tatiana. “How ants turn information into food.” 2015. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/37.
MLA Handbook (7th Edition):
Flanagan, Tatiana. “How ants turn information into food.” 2015. Web. 18 Jul 2019.
Vancouver:
Flanagan T. How ants turn information into food. [Internet] [Doctoral dissertation]. University of New Mexico; 2015. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/37.
Council of Science Editors:
Flanagan T. How ants turn information into food. [Doctoral Dissertation]. University of New Mexico; 2015. Available from: https://digitalrepository.unm.edu/biol_etds/37
University of New Mexico
12.
Roy, Sushmita.
Learning condition-specific networks.
Degree: Department of Computer Science, 2009, University of New Mexico
URL: http://hdl.handle.net/1928/10331
► Condition-specific cellular networks are networks of genes and proteins that describe functional interactions among genes occurring under different environmental conditions. These networks provide a systems-level…
(more)
▼ Condition-specific cellular networks are networks of genes and proteins that describe functional interactions among genes occurring under different environmental conditions. These networks provide a systems-level view of how the parts-list (genes and proteins) interact within the cell as it functions under changing environmental conditions and can provide insight into mechanisms of stress response, cellular differentiation and disease susceptibility. The principle challenge, however, is that cellular networks remain unknown for most conditions and must be inferred from activity levels of genes (mRNA levels) under different conditions. This dissertation aims to develop computational approaches for inferring, analyzing and validating cellular networks of genes from expression data. This dissertation first describes an unsupervised machine learning framework for inferring cellular networks using expression data from a single condition. Here cellular networks are represented as undirected probabilistic graphical models and are learned using a novel, data-driven algorithm. Then several approaches are described that can learn networks using data from multiple conditions. These approaches apply to cases where the condition may or may not be known and, therefore, must be inferred as part of the learning problem. For the latter, the condition variable is allowed to influence expression of genes at different levels of granularity: condition variable per gene to a single condition variable for all genes. Results on simulated data suggest that the algorithm performance depends greatly on the size and number of connected components of the union network of all conditions. These algorithms are also applied to microarray data from two yeast populations, quiescent and non-quiescent, isolated from glucose starved cultures. Our results suggest that by sharing information across multiple conditions, better networks can be learned for both conditions, with many more biologically meaningful dependencies, than if networks were learned for these conditions independently. In particular, processes that were shared among both cell populations were involved in response to glucose starvation, whereas the processes specific to individual populations captured characteristics unique to each population. These algorithms were also applied for learning networks across multiple species: yeast (S. cerevisiae) and fly (D. melanogaster). Preliminary analysis suggests that sharing patterns across species is much more complex than across different populations of the same species and basic metabolic processes are shared across the two species. Finally, this dissertation focuses on validation of cellular networks. This validation framework describes scores for measuring how well network learning algorithms capture higher-order dependencies. This framework also introduces a measure for evaluating the entire inferred network structure based on the extent to which similarly functioning genes are close together on the network.
Advisors/Committee Members: Lane, Terran, Werner-Washburne, Margaret, Moses, Melanie, Atlas, Susan.
Subjects/Keywords: Machine learning; Computational Biology; Probabilistic graphical models; Gene expression; Condition-specific response
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APA (6th Edition):
Roy, S. (2009). Learning condition-specific networks. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/10331
Chicago Manual of Style (16th Edition):
Roy, Sushmita. “Learning condition-specific networks.” 2009. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/10331.
MLA Handbook (7th Edition):
Roy, Sushmita. “Learning condition-specific networks.” 2009. Web. 18 Jul 2019.
Vancouver:
Roy S. Learning condition-specific networks. [Internet] [Doctoral dissertation]. University of New Mexico; 2009. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/10331.
Council of Science Editors:
Roy S. Learning condition-specific networks. [Doctoral Dissertation]. University of New Mexico; 2009. Available from: http://hdl.handle.net/1928/10331
University of New Mexico
13.
Bezerra, George.
Energy consumption in networks on chip : efficiency and scaling.
Degree: Department of Computer Science, 2012, University of New Mexico
URL: http://hdl.handle.net/1928/21020
► Computer architecture design is in a new era where performance is increased by replicating processing cores on a chip rather than making CPUs larger and…
(more)
▼ Computer architecture design is in a
new era where performance is increased by replicating processing cores on a chip rather than making CPUs larger and faster. This design strategy is motivated by the superior energy efficiency of the multi-core architecture compared to the traditional monolithic CPU. If the trend continues as expected, the number of cores on a chip is predicted to grow exponentially over time as the density of transistors on a die increases. A major challenge to the efficiency of multi-core chips is the energy used for communication among cores over a Network on Chip (NoC). As the number of cores increases, this energy also increases, imposing serious constraints on design and performance of both applications and architectures. Therefore, understanding the impact of different design choices on NoC power and energy consumption is crucial to the success of the multi- and many-core designs. This dissertation proposes methods for modeling and optimizing energy consumption in multi- and many-core chips, with special focus on the energy used for communication on the NoC. We present a number of tools and models to optimize energy consumption and model its scaling behavior as the number of cores increases. We use synthetic traffic patterns and full system simulations to test and validate our methods. Finally, we take a step back and look at the evolution of computer hardware in the last 40 years and, using a scaling theory from biology, present a predictive theory for power-performance scaling in microprocessor systems.
Advisors/Committee Members: Forrest, Stephanie, Moses, Melanie, Arnold, Dorian, Zarkesh-Ha, Payman.
Subjects/Keywords: multi-core; many-core; energy consumption; communicaiton locality; scaling
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APA (6th Edition):
Bezerra, G. (2012). Energy consumption in networks on chip : efficiency and scaling. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/21020
Chicago Manual of Style (16th Edition):
Bezerra, George. “Energy consumption in networks on chip : efficiency and scaling.” 2012. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/21020.
MLA Handbook (7th Edition):
Bezerra, George. “Energy consumption in networks on chip : efficiency and scaling.” 2012. Web. 18 Jul 2019.
Vancouver:
Bezerra G. Energy consumption in networks on chip : efficiency and scaling. [Internet] [Doctoral dissertation]. University of New Mexico; 2012. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/21020.
Council of Science Editors:
Bezerra G. Energy consumption in networks on chip : efficiency and scaling. [Doctoral Dissertation]. University of New Mexico; 2012. Available from: http://hdl.handle.net/1928/21020
University of New Mexico
14.
Villalon, Ricardo.
Fault-tolerant wireless sensor networks using evolutionary games.
Degree: Department of Computer Science, 2012, University of New Mexico
URL: http://hdl.handle.net/1928/22075
► This dissertation proposes an approach to creating robust communication systems in wireless sensor networks, inspired by biological and ecological systems, particularly by evolutionary game theory.…
(more)
▼ This dissertation proposes an approach to creating robust communication systems in wireless sensor networks, inspired by biological and ecological systems, particularly by evolutionary game theory. In this approach, a virtual community of agents live inside the network nodes and carry out network functions. The agents use different strategies to execute their functions, and these strategies are tested and selected by playing evolutionary games. Over time, agents with the best strategies survive, while others die. The strategies and the game rules provide the network with an adaptive behavior that allows it to react to changes in environmental conditions by adapting and improving network behavior. To evaluate the viability of this approach, this dissertation also describes a micro-component framework for implementing agent-based wireless sensor network services, an evolutionary data collection protocol built using this framework, ECP, and experiments evaluating the performance of this protocol in a faulty environment. The framework addresses many of the programming challenges in writing network software for wireless sensor networks, while the protocol built using the framework provides a means of evaluating the general viability of the agent-based approach. The results of this evaluation show that an evolutionary approach to designing wireless sensor networks can improve the performance of wireless sensor network protocols in the presence of node failures. In particular, we compared the performance of ECP with a non-evolutionary rule-based variant of ECP. While the purely-evolutionary version of ECP has more routing timeouts than the rule-based approach in failure-free networks, it sends significantly fewer beacon packets and incurs statistically fewer routing timeouts in both simple fault and periodic fault scenarios.
Advisors/Committee Members: Bridges, Patrick, Moses, Melanie, Ackley, David, Caudell, Thomas.
Subjects/Keywords: Wireless Sensor Networks; Agent-based systems
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APA (6th Edition):
Villalon, R. (2012). Fault-tolerant wireless sensor networks using evolutionary games. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/22075
Chicago Manual of Style (16th Edition):
Villalon, Ricardo. “Fault-tolerant wireless sensor networks using evolutionary games.” 2012. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/22075.
MLA Handbook (7th Edition):
Villalon, Ricardo. “Fault-tolerant wireless sensor networks using evolutionary games.” 2012. Web. 18 Jul 2019.
Vancouver:
Villalon R. Fault-tolerant wireless sensor networks using evolutionary games. [Internet] [Doctoral dissertation]. University of New Mexico; 2012. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/22075.
Council of Science Editors:
Villalon R. Fault-tolerant wireless sensor networks using evolutionary games. [Doctoral Dissertation]. University of New Mexico; 2012. Available from: http://hdl.handle.net/1928/22075
University of New Mexico
15.
Levin, Drew.
The Environment Constrains Successful Search Strategies in Natural Distributed Systems.
Degree: Department of Computer Science, 2016, University of New Mexico
URL: http://hdl.handle.net/1928/32313
► This dissertation investigates two natural systems that use distributed search algorithms and tests the hypothesis that the searchers' environment is a key constraint on an…
(more)
▼ This dissertation investigates two natural systems that use distributed search algorithms and tests the hypothesis that the searchers' environment is a key constraint on an optimal algorithm. Natural instances of distributed autonomous systems of simple components exist in both biology and social systems. These systems have been honed through eons of evolution by natural selection to perform well in their environment. I examine two specific systems that use distributed methods to search and recruit individuals to locations of interest: T cells' search for pathogens in the human body and ants searching for food. Both systems are examples of time-constrained processes that require the distributed coordination of simple autonomous agents and interaction with their environment. Taking common principles from both domains, the dissertation examines three distributed search strategies: uninformed random search, origin-based local recruitment, and chemical-based pheromone recruitment. Using both numerical and agent-based models, it evaluates the effectiveness of these strategies across two environmental factors: the spatial clustering and temporal volatility of resources. The results demonstrate that both recruitment-based strategies (origin-based and chemical-based) suffer in environments of high resources dispersion and volatility. Conversely, uninformed random search performs better in these environments. The results are relevant to certain algorithmic issues in swarm robotics. For example, it is expensive to implement chemical trails in a distributed physical system, and the dissertation shows that strategies using only local recruitment perform similarly in all environments. Also, origin-only algorithms are much easier to implement in a robotics context. Further, because each strategy examined in this dissertation performs best at one extreme of resource spatial distribution, the results establish that the most difficult environments for search are likely those with intermediate levels of clustering. Finally, the dissertation classifies the exact nature of the environmental trade-offs and presents methods to determine the best search strategy given knowledge of the environment.
Advisors/Committee Members: Forrest, Stephanie, Moses, Melanie, Tapia, Lydia, Cannon, Judy.
Subjects/Keywords: Distributed Systems; Distributed Search; Computational Biology; Theoretical Biology; Immunology; Virology; Myrmecology
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APA (6th Edition):
Levin, D. (2016). The Environment Constrains Successful Search Strategies in Natural Distributed Systems. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/32313
Chicago Manual of Style (16th Edition):
Levin, Drew. “The Environment Constrains Successful Search Strategies in Natural Distributed Systems.” 2016. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/32313.
MLA Handbook (7th Edition):
Levin, Drew. “The Environment Constrains Successful Search Strategies in Natural Distributed Systems.” 2016. Web. 18 Jul 2019.
Vancouver:
Levin D. The Environment Constrains Successful Search Strategies in Natural Distributed Systems. [Internet] [Doctoral dissertation]. University of New Mexico; 2016. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/32313.
Council of Science Editors:
Levin D. The Environment Constrains Successful Search Strategies in Natural Distributed Systems. [Doctoral Dissertation]. University of New Mexico; 2016. Available from: http://hdl.handle.net/1928/32313
University of New Mexico
16.
Letendre, Kenneth.
Simulating the evolution of recruitment behavior in foraging Ants.
Degree: Department of Computer Science, 2010, University of New Mexico
URL: http://hdl.handle.net/1928/12049
► Spatial heterogeneity in the distribution of food is an important determinant of species' optimal foraging strategies, and of the dynamics of populations and communities. In…
(more)
▼ Spatial heterogeneity in the distribution of food is an important determinant of species' optimal foraging strategies, and of the dynamics of populations and communities. In order to explore the interaction of food heterogeneity and colony size in their effects on the behavior of foraging ant colonies, we built agent-based models of the foraging and recruitment behavior of harvester ants of the genus Pogonomyrmex. We optimized the behavior of these models using genetic algorithms over a variety of food distributions and colony sizes, and validated their behavior by comparison with data collected on harvester ants foraging for seeds in the field. We compared two models: one in which ants lay a pheromone trail each time they return to the nest with food; and another in which ants lay pheromone trails selectively, depending on the density of other food available in the area where food was found. We found that the density-dependent trail-laying model fit the field data better. We found that in this density-dependent recruitment model, colonies of all sizes evolved intense recruitment behavior, even when optimized for environments in which the majority of foods are distributed homogeneously. We discuss the implications of these models to the understanding of optimal foraging strategy and community dynamics among ants, and potential for application to ACO and other distributed problem-solving systems.
Advisors/Committee Members: Moses, Melanie, Forrest, Stephanie, Watson, Paul.
Subjects/Keywords: Ants; Distributed-Problem Solving; Foraging; Genetic Algorithm; Optimization; Recruitment
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APA (6th Edition):
Letendre, K. (2010). Simulating the evolution of recruitment behavior in foraging Ants. (Masters Thesis). University of New Mexico. Retrieved from http://hdl.handle.net/1928/12049
Chicago Manual of Style (16th Edition):
Letendre, Kenneth. “Simulating the evolution of recruitment behavior in foraging Ants.” 2010. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/12049.
MLA Handbook (7th Edition):
Letendre, Kenneth. “Simulating the evolution of recruitment behavior in foraging Ants.” 2010. Web. 18 Jul 2019.
Vancouver:
Letendre K. Simulating the evolution of recruitment behavior in foraging Ants. [Internet] [Masters thesis]. University of New Mexico; 2010. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/12049.
Council of Science Editors:
Letendre K. Simulating the evolution of recruitment behavior in foraging Ants. [Masters Thesis]. University of New Mexico; 2010. Available from: http://hdl.handle.net/1928/12049
University of New Mexico
17.
Flynn, Mark.
Improving peer review with ACORN : Ant Colony Optimization algorithm for Reviewer's Network.
Degree: Department of Computer Science, 2011, University of New Mexico
URL: http://hdl.handle.net/1928/13085
► Peer review, our current system for determining which papers to accept and which to reject by journals and conferences, has limitations that impair the quality…
(more)
▼ Peer review, our current system for determining which papers to accept and which to reject by journals and conferences, has limitations that impair the quality of scientific communication. Under the current system, reviewers have only a limited amount of time to devote to evaluating papers and each paper receives an equal amount of attention regardless of how good the paper is. We propose to implement a
new system for conference peer review based on ant colony optimization (ACO) algorithms. In our model, each reviewer has a set of ants that goes out and finds articles. The reviewer assesses the paper that the ant brings according to the criteria specified by the conference organizers and the ant deposits pheromone that is proportional to the quality of the review. Each subsequent ant then samples the pheromones and probabilistically selects the next article based on the strength of the pheromones. We used an agent-based model to determine if an ACO-based paper selection system will direct reviewers attention to the best articles and if the average quality of papers increases with each round of reviews. We also conducted an experiment in conjunction with the 2011 UNM Computer Science Graduate Student Association conference and compared the results with our simulation. To assess the usefulness of our approach, we compared our algorithm to a greedy algorithm that always takes the best un-reviewed paper and a latent factor analysis recommender-based system. We found that the ACO-based algorithm was better than either of the greedy or recommender algorithms at directing users' attention to the better papers.
Advisors/Committee Members: Moses, Melanie, Luger, George, Greene, Kshanti.
Subjects/Keywords: Ant Colony Optimization; Peer review
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APA (6th Edition):
Flynn, M. (2011). Improving peer review with ACORN : Ant Colony Optimization algorithm for Reviewer's Network. (Masters Thesis). University of New Mexico. Retrieved from http://hdl.handle.net/1928/13085
Chicago Manual of Style (16th Edition):
Flynn, Mark. “Improving peer review with ACORN : Ant Colony Optimization algorithm for Reviewer's Network.” 2011. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/13085.
MLA Handbook (7th Edition):
Flynn, Mark. “Improving peer review with ACORN : Ant Colony Optimization algorithm for Reviewer's Network.” 2011. Web. 18 Jul 2019.
Vancouver:
Flynn M. Improving peer review with ACORN : Ant Colony Optimization algorithm for Reviewer's Network. [Internet] [Masters thesis]. University of New Mexico; 2011. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/13085.
Council of Science Editors:
Flynn M. Improving peer review with ACORN : Ant Colony Optimization algorithm for Reviewer's Network. [Masters Thesis]. University of New Mexico; 2011. Available from: http://hdl.handle.net/1928/13085
University of New Mexico
18.
Stolleis, Karl.
The Ant and the Trap: Evolution of Ant-Inspired Obstacle Avoidance in a Multi-Agent Robotic System.
Degree: Department of Computer Science, 2015, University of New Mexico
URL: http://hdl.handle.net/1928/27969
► Interest in swarm robotics, particularly those modeled on biological systems, has been increasing with each passing year. We created the iAnt robot as a platform…
(more)
▼ Interest in swarm robotics, particularly those modeled on biological systems, has been increasing with each passing year. We created the iAnt robot as a platform to test how well an ant-inspired robotic swarm could collect resources in an unmapped environment. Although swarm robotics is still a loosely defined field, one of the included hallmarks is multiple robots cooperating to complete a given task. The use of multiple robots means increased cost for research, scaling often linearly with the number of robots. We set out to create a system with the previously described capabilities while lowering the entry cost by building simple, cheap robots able to operate outside of a dedicated lab environment. Obstacle avoidance has long been a necessary component of robot systems. Avoiding collisions is also a difficult problem and has been studied for many years. As part of moving the iAnt further towards the real-world we needed a method of obstacle avoidance. Our hypothesis is that use of biological methods including evolution, stochastic movements and stygmergic trails into the iAnt Central Place Foraging Algorithm (CPFA) could result in robot behaviors suited to navigating obstacle-filled environments. The result is a modification of the CPFA to include pheromone trails, CPFA-Trails or CPFAT. This thesis first demonstrates the low-cost, simple and robust design of the physical iAnt robot. Secondly we will demonstrate the adaptability of the the system to evolve and succeed in an obstacle-laden environment.
Advisors/Committee Members: Moses, Melanie, Tapia, Lydia, Fierro, Rafael.
Subjects/Keywords: robot; swarm robotics; ant; genetic algorithm; foraging; obstacle avoidance; biologically inspired; in situ resource utilization; evolution; robot behavior
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APA (6th Edition):
Stolleis, K. (2015). The Ant and the Trap: Evolution of Ant-Inspired Obstacle Avoidance in a Multi-Agent Robotic System. (Masters Thesis). University of New Mexico. Retrieved from http://hdl.handle.net/1928/27969
Chicago Manual of Style (16th Edition):
Stolleis, Karl. “The Ant and the Trap: Evolution of Ant-Inspired Obstacle Avoidance in a Multi-Agent Robotic System.” 2015. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/27969.
MLA Handbook (7th Edition):
Stolleis, Karl. “The Ant and the Trap: Evolution of Ant-Inspired Obstacle Avoidance in a Multi-Agent Robotic System.” 2015. Web. 18 Jul 2019.
Vancouver:
Stolleis K. The Ant and the Trap: Evolution of Ant-Inspired Obstacle Avoidance in a Multi-Agent Robotic System. [Internet] [Masters thesis]. University of New Mexico; 2015. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/27969.
Council of Science Editors:
Stolleis K. The Ant and the Trap: Evolution of Ant-Inspired Obstacle Avoidance in a Multi-Agent Robotic System. [Masters Thesis]. University of New Mexico; 2015. Available from: http://hdl.handle.net/1928/27969
University of New Mexico
19.
Arora, Tamanna.
Using ant colony optimization for routing in microprocesors.
Degree: Department of Computer Science, 2009, University of New Mexico
URL: http://hdl.handle.net/1928/10258
► Power consumption is an important constraint on VLSI systems. With the advancement in technology, it is now possible to pack a large range of functionalities…
(more)
▼ Power consumption is an important constraint on VLSI systems. With the advancement in technology, it is now possible to pack a large range of functionalities into VLSI devices. Hence it is important to find out ways to utilize these functionalities with optimized power consumption. This work focuses on curbing power consumption at the design stage. This work emphasizes minimizing active power consumption by minimizing the load capacitance of the chip. Capacitance of wires and vias can be minimized using Ant Colony Optimization (ACO) algorithms. ACO provides a multi agent framework for combinatorial optimization problems and hence is used to handle multiple constraints of minimizing wire-length and vias to achieve the goal of minimizing capacitance and hence power consumption. The ACO developed here is able to achieve an 8% reduction of wire-length and 7% reduction in vias thereby providing a 7% reduction in total capacitance, compared to other state of the art routers.
Advisors/Committee Members: Moses, Melanie, Luger, George F., Zarkesh-Ha, Payman.
Subjects/Keywords: VLSI; Routing; ACO
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APA (6th Edition):
Arora, T. (2009). Using ant colony optimization for routing in microprocesors. (Masters Thesis). University of New Mexico. Retrieved from http://hdl.handle.net/1928/10258
Chicago Manual of Style (16th Edition):
Arora, Tamanna. “Using ant colony optimization for routing in microprocesors.” 2009. Masters Thesis, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/10258.
MLA Handbook (7th Edition):
Arora, Tamanna. “Using ant colony optimization for routing in microprocesors.” 2009. Web. 18 Jul 2019.
Vancouver:
Arora T. Using ant colony optimization for routing in microprocesors. [Internet] [Masters thesis]. University of New Mexico; 2009. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/10258.
Council of Science Editors:
Arora T. Using ant colony optimization for routing in microprocesors. [Masters Thesis]. University of New Mexico; 2009. Available from: http://hdl.handle.net/1928/10258
University of New Mexico
20.
Faust, Aleksandra.
Reinforcement Learning and Planning for Preference Balancing Tasks.
Degree: Department of Computer Science, 2014, University of New Mexico
URL: http://hdl.handle.net/1928/24551
► Robots are often highly non-linear dynamical systems with many degrees of freedom, making solving motion problems computationally challenging. One solution has been reinforcement learning (RL),…
(more)
▼ Robots are often highly non-linear dynamical systems with many degrees of freedom, making solving motion problems computationally challenging. One solution has been reinforcement learning (RL), which learns through experimentation to automatically perform the near-optimal motions that complete a task. However, high-dimensional problems and task formulation often prove challenging for RL. We address these problems with PrEference Appraisal Reinforcement Learning (PEARL), which solves Preference Balancing Tasks (PBTs). PBTs define a problem as a set of preferences that the system must balance to achieve a goal. The method is appropriate for acceleration-controlled systems with continuous state-space and either discrete or continuous action spaces with unknown system dynamics. We show that PEARL learns a sub-optimal policy on a subset of states and actions, and transfers the policy to the expanded domain to produce a more refined plan on a class of robotic problems. We establish convergence to task goal conditions, and even when preconditions are not verifiable, show that this is a valuable method to use before other more expensive approaches. Evaluation is done on several robotic problems, such as Aerial Cargo Delivery, Multi-Agent Pursuit, Rendezvous, and Inverted Flying Pendulum both in simulation and experimentally. Additionally, PEARL is leveraged outside of robotics as an array sorting agent. The results demonstrate high accuracy and fast learning times on a large set of practical applications.
Advisors/Committee Members: Tapia, Lydia, Estrada, Trilce, Fierro, Rafael, Moses, Melanie, Williams, Lance.
Subjects/Keywords: Reinforcement learning; Motion planning; Robotics; Artificial Intelligence; Unmanned Aerial Vehcile; Systems control
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APA (6th Edition):
Faust, A. (2014). Reinforcement Learning and Planning for Preference Balancing Tasks. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/24551
Chicago Manual of Style (16th Edition):
Faust, Aleksandra. “Reinforcement Learning and Planning for Preference Balancing Tasks.” 2014. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/24551.
MLA Handbook (7th Edition):
Faust, Aleksandra. “Reinforcement Learning and Planning for Preference Balancing Tasks.” 2014. Web. 18 Jul 2019.
Vancouver:
Faust A. Reinforcement Learning and Planning for Preference Balancing Tasks. [Internet] [Doctoral dissertation]. University of New Mexico; 2014. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/24551.
Council of Science Editors:
Faust A. Reinforcement Learning and Planning for Preference Balancing Tasks. [Doctoral Dissertation]. University of New Mexico; 2014. Available from: http://hdl.handle.net/1928/24551
University of New Mexico
21.
Letendre, Kenneth.
Variation and organization in social behavior : infectious disease and human intergroup conflict and warfare; and the organization of foraging behavior in harvester ants.
Degree: UNM Biology Department, 2012, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/70
► Social behavior is an important contributor to the success of widely distributed animal taxa, including such distantly related taxa as humans and ants. There is…
(more)
▼ Social behavior is an important
contributor to the success of widely distributed animal taxa, including such distantly related taxa as humans and ants. There is variation in the features and organization of social systems based on ecological constraints and goals, as these alter the costs and benefits of social behaviors, and select for different optimal behaviors for social groups in different environments. I present two bodies of research: an effort to explain geographic variation in the frequency and intensity of human civil conflict; and an effort to describe and model the foraging behavior of colonies of harvester ants of the genus Pogonomyrmex. First, in an investigation of the geographic variation in the frequency of human civil conflict, I show that cross-nationally, intrastate armed conflicts are predicted positively by variation in the intensity of human infectious disease. I present a theoretical model to explain this variation that proposes that risk of exposure to novel infectious diseases imposes costs on intergroup social interaction, and in regions with high intensity of infectious disease these costs create relative poverty and exacerbate conflict over resources. Second, I show that infectious disease predicts other categories of civil conflict, including clan wars, and revolutions and coups. I present a path analysis of the global peace index to test the plausibility of the hypothesized model, including the various indirect effects linking infectious disease to conflict; this analysis supports the importance of the relationship between infectious disease and conflict cross-nationally. Third, I present the results of a study using a computer model of host-parasite coevolution to examine the mechanisms by which localized host-parasite coevolutionary races impose fitness costs on host intergroup interaction, and lead to the evolution of out-group avoidance in mating decisions. In the fourth chapter I present a field study of the foraging behavior of three sympatric species of harvester ants, and their response to variation in heterogeneity in the distribution of foods. Fifth, I present a computer model of ant colony foraging behavior, which I optimized using genetic algorithms for different distributions of food, and whose resulting foraging behavior I compare to the previous observations of harvester ants in the field.
Advisors/Committee Members: Thornhill, Randy, Watson, Paul, Gangestad, Steve, Kodric-Brown, Astrid, Moses, Melanie.
Subjects/Keywords: human warfare; competition; inter-group violence; political values; evolution; behavior; infectious disease; harvester ants; foraging ecology; agent-based modeling
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APA (6th Edition):
Letendre, K. (2012). Variation and organization in social behavior : infectious disease and human intergroup conflict and warfare; and the organization of foraging behavior in harvester ants. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/70
Chicago Manual of Style (16th Edition):
Letendre, Kenneth. “Variation and organization in social behavior : infectious disease and human intergroup conflict and warfare; and the organization of foraging behavior in harvester ants.” 2012. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/70.
MLA Handbook (7th Edition):
Letendre, Kenneth. “Variation and organization in social behavior : infectious disease and human intergroup conflict and warfare; and the organization of foraging behavior in harvester ants.” 2012. Web. 18 Jul 2019.
Vancouver:
Letendre K. Variation and organization in social behavior : infectious disease and human intergroup conflict and warfare; and the organization of foraging behavior in harvester ants. [Internet] [Doctoral dissertation]. University of New Mexico; 2012. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/70.
Council of Science Editors:
Letendre K. Variation and organization in social behavior : infectious disease and human intergroup conflict and warfare; and the organization of foraging behavior in harvester ants. [Doctoral Dissertation]. University of New Mexico; 2012. Available from: https://digitalrepository.unm.edu/biol_etds/70
University of New Mexico
22.
Wenyun, Zuo.
From growth to extinction : explored by life history and metabolic theory.
Degree: UNM Biology Department, 2011, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/111
► The laws of energy and material conservation are fundamental principles across various scales and systems. Based on the conservation laws, I derive several theoretical models…
(more)
▼ The laws of energy and material conservation are fundamental principles across various scales and systems. Based on the conservation laws, I derive several theoretical models to understand mechanisms behind the energy budget of ontogenetic growth and the pattern of the late Pleistocene extinction of megafauna in the Americas. First, I present a model, empirically grounded in data from birds and mammals, that correctly predicts how growing animals allocate food energy between synthesis of
new biomass and maintenance of existing biomass. Previous energy budget models have typically been based on rates of either food consumption or metabolic energy expenditure. The model provides a framework that reconciles these two approaches and highlights the fundamental principles that determine rates of food assimilation and rates of energy allocation to maintenance, biosynthesis, activity, and storage. The model predicts that growth and assimilation rates for all animals should cluster closely around two canonical curves. Second, the previous model, which focuses on endotherms, has been extended to understand effects of temperature on the energy budget of ontogenetic growth of ectotherms. A tendency for ectotherms to develop faster but mature at smaller body sizes in warmer environments has been studied for decades, and is called the temperature size rule (TSR). It can be explained by a simple model in which the rate of growth or biomass accumulation and the rate of development or differentiation have different temperature dependence. The model accounts for both TSR and the less frequently observed reverse-TSR, predicts the fraction of energy allocated to maintenance and synthesis over the course of development, and the temperature independent growth efficiency. It also predicts that less total energy is expended when developing at warmer temperatures for TSR and vice versa for reverse-TSR. It has important implications for effects of climate change on ectothermic animals and also provides how selection may lead to the evolution of both TSR and reverse-TSR. Finally, based on mammalian life history and life history scaling relationships, an exploitation-extinction theory has been developed for the rate of human harvest in the disappearance of the Pleistocene megafauna in the Americas. The theory demonstrates that the added mortality of human harvest on populations need not be selective to produce a size-biased extinction. The variation in the adult natural instantaneous mortality rate and/or the maximum recruitment compensation at any body mass are main components determining the probability of extinction. The theory successfully predicts the shapes of the extinction probability curves for the late Pleistocene extinction in the Americas. It provides a theoretical basis to challenge a major criticism of the "overkill" theory that early Paleoindian hunters had to be extremely selective to have produced the highly size-biased pattern characteristic to the late Pleistocene extinction of megafauna in the Americas.
Advisors/Committee Members: Brown, James H., West, Geoffrey B., Moses, Melanie E., Wearing, Helen.
Subjects/Keywords: energy budget; endotherm; ectotherm; late Pleistocene; the effect of temperature
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APA (6th Edition):
Wenyun, Z. (2011). From growth to extinction : explored by life history and metabolic theory. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/111
Chicago Manual of Style (16th Edition):
Wenyun, Zuo. “From growth to extinction : explored by life history and metabolic theory.” 2011. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/111.
MLA Handbook (7th Edition):
Wenyun, Zuo. “From growth to extinction : explored by life history and metabolic theory.” 2011. Web. 18 Jul 2019.
Vancouver:
Wenyun Z. From growth to extinction : explored by life history and metabolic theory. [Internet] [Doctoral dissertation]. University of New Mexico; 2011. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/111.
Council of Science Editors:
Wenyun Z. From growth to extinction : explored by life history and metabolic theory. [Doctoral Dissertation]. University of New Mexico; 2011. Available from: https://digitalrepository.unm.edu/biol_etds/111
University of New Mexico
23.
Kanigel Winner, Kimberly Rene.
Multi-scale models of ovarian cancer.
Degree: UNM Biology Department, 2015, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/58
► In ovarian cancer, disease and treatment can be examined across multiple spatial scales including molecules, cells, intra-tumor vasculature, and body-scale dynamics of circulating drugs.…
(more)
▼ In ovarian cancer, disease and treatment can be examined across multiple spatial scales including molecules, cells, intra-tumor vasculature, and body-scale dynamics of circulating drugs. Survival of primary tumor cells and their development into disseminated tumors is related to adhesion between the cells, attachment, and invasion. Growth of
new tumors depends on the delivery of nutrients, which depends on the tumor diameter and the tumors vasculature. Drug delivery also depends on tumor diameter and vasculature, and molecular- and gross-scale drug processes. A cellular Potts simulation integrated data at these multiple scales to model microscopic residual disease during relapse after a primary surgery. The model generated
new hypotheses about tumor cell behavior, and the effectiveness of drug delivery to tumors disseminated in the peritoneal cavity. First, the model required high intra-tumor adhesion in ovarian tumors, the existence of an unknown factor that drew tumor cells to vessels, a threshold of vascular endothelial growth factor (VEGF) for initiation of endothelial sprouting, and constitutive expression of angiogenic chemical messengers by tumor cells prior to needing oxygen. Alteration of the model incorporated drug delivery by the two standard routes, intraperitoneal and intravenous, from tumor vasculature parameterized from real patient data. Delivery of both small- and large-molecular weight therapies was superior during intraperitoneal therapy. Finally, empirical and theoretical distributions of vessel radii were considered. Samples from tumors with each type of vascular morphology were run as though too distant from the peritoneal cavity to receive peritoneal delivery, with three results: first, intravenous delivery was superior to the secondary delivery into the circulatory system from a primary intraperitoneal delivery. Second, small molecules penetrated homogeneously across all cells, regardless of vascular volume or morphology, while antibodies penetrated heterogeneously, particularly in low-vessel-volume samples. Third, when each of the whole tumors was considered, this heterogeneity resulted in a large sub-population of cells that accumulated non-therapeutic levels of antibody, even during the best delivery scenario (IV). Fourth, delivery of antibodies was poorest in the empirical distribution. Finally, hypotheses were generated about the impact of heterogeneity of drug delivery, to be addressed as future questions.
Advisors/Committee Members: Moses, Melanie, Wearing, Helen, Jiang, Yi, Wilson, Bridget S., Wearing, Helen.
Subjects/Keywords: multi-scale; cellular Potts; ovarian cancer; ErbB2; drug delivery; vascularization; tumor modeling; Biology
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APA (6th Edition):
Kanigel Winner, K. R. (2015). Multi-scale models of ovarian cancer. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/58
Chicago Manual of Style (16th Edition):
Kanigel Winner, Kimberly Rene. “Multi-scale models of ovarian cancer.” 2015. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/58.
MLA Handbook (7th Edition):
Kanigel Winner, Kimberly Rene. “Multi-scale models of ovarian cancer.” 2015. Web. 18 Jul 2019.
Vancouver:
Kanigel Winner KR. Multi-scale models of ovarian cancer. [Internet] [Doctoral dissertation]. University of New Mexico; 2015. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/58.
Council of Science Editors:
Kanigel Winner KR. Multi-scale models of ovarian cancer. [Doctoral Dissertation]. University of New Mexico; 2015. Available from: https://digitalrepository.unm.edu/biol_etds/58
University of New Mexico
24.
Greene, Kshanti.
Collective belief models for representing consensus and divergence in communities of Bayesian decision-makers.
Degree: Department of Computer Science, 2010, University of New Mexico
URL: http://hdl.handle.net/1928/10878
► Bayesian belief aggregation is the process of forming a consensus model from the probabilistic beliefs of multiple individuals. Preference aggregation attempts to find an optimal…
(more)
▼ Bayesian belief aggregation is the process of forming a consensus model from the probabilistic beliefs of multiple individuals. Preference aggregation attempts to find an optimal solution for a population considering each individual's beliefs, desires and objectives. Belief and preference aggregation approaches that form a single consensus average away any diversity in a population. In the process they may fail to uphold a set of mathematical properties for rational aggregation defined by social choice theorists. This dissertation introduces a
new aggregation approach that maintains the diversity of a population and allows the competitive aspects of a situation to emerge, enabling game theoretic analysis in large populations of decision-makers. Each individual's beliefs and preferences are represented by a Bayesian network. Based on the result of inference on the networks, a population is separated into collectives whose members agree on the relatively likelihood or desirability of the possible outcomes of a situation. An aggregate for each collective can then be computed such that the aggregate upholds the rationality properties. Game theoretic analysis is then applied using 'super-agents' that represent each collective as the game players. In this manner, the set of Pareto optimal and Nash equilibrium solutions can be found, even in situations that cause single consensus models to return non-Pareto or otherwise 'irrational' solutions.
Advisors/Committee Members: Luger, George, Kniss, Joe, Moses, Melanie, Ross, Tim, Stern, Carl.
Subjects/Keywords: Decision-making; Bayesian reasoning; Social choice theory; Probabilistic reasoning; Bayesian belief aggregation; game theory; diversity; artificial intelligence; social decision-making
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APA (6th Edition):
Greene, K. (2010). Collective belief models for representing consensus and divergence in communities of Bayesian decision-makers. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/10878
Chicago Manual of Style (16th Edition):
Greene, Kshanti. “Collective belief models for representing consensus and divergence in communities of Bayesian decision-makers.” 2010. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/10878.
MLA Handbook (7th Edition):
Greene, Kshanti. “Collective belief models for representing consensus and divergence in communities of Bayesian decision-makers.” 2010. Web. 18 Jul 2019.
Vancouver:
Greene K. Collective belief models for representing consensus and divergence in communities of Bayesian decision-makers. [Internet] [Doctoral dissertation]. University of New Mexico; 2010. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/10878.
Council of Science Editors:
Greene K. Collective belief models for representing consensus and divergence in communities of Bayesian decision-makers. [Doctoral Dissertation]. University of New Mexico; 2010. Available from: http://hdl.handle.net/1928/10878
University of New Mexico
25.
Malone, Nick D.
High-Dimensional Motion Planning and Learning Under Uncertain Conditions.
Degree: Department of Computer Science, 2015, University of New Mexico
URL: http://hdl.handle.net/1928/31730
► Many existing path planning methods do not adequately account for uncertainty. Without uncertainty these existing techniques work well, but in real world environments they struggle…
(more)
▼ Many existing path planning methods do not adequately account for uncertainty. Without uncertainty these existing techniques work well, but in real world environments they struggle due to inaccurate sensor models, arbitrarily moving obstacles, and uncertain action consequences. For example, picking up and storing childrens toys is a simple task for humans. Yet, for a robotic household robot the task can be daunting. The room must be modeled with sensors, which may or may not detect all the strewn toys. The robot must be able to detect and avoid the child who may be moving the very toys that the robot is tasked with cleaning. Finally, if the robot missteps and places a foot on a toy, it must be able to compensate for the unexpected consequences of its actions. This example demonstrates that even simple human tasks are fraught with uncertainties that must be accounted for in robotic path planning algorithms. This work presents the first steps towards migrating sampling-based path planning methods to real world environments by addressing three different types of uncertainty: (1) model uncertainty, (2) spatio-temporal obstacle uncertainty (moving obstacles) and (3) action consequence uncertainty. Uncertainty is encoded directly into path planning through a data structure in order to successfully and efficiently identify safe robot paths in sensed environments with noise. This encoding produces comparable clearance paths to other planning methods which are a known for high clearance, but at an order of magnitude less computational cost. It also shows that formal control theory methods combined with path planning provides a technique that has a 95% collision-free navigation rate with 300 moving obstacles. Finally, it demonstrates that reinforcement learning can be combined with planning data structures to autonomously learn motion controls of a seven degree of freedom robot despite a low computational cost despite the number of dimensions.
Advisors/Committee Members: Tapia, Lydia, Wood, John, Kapur, Deepak, Moses, Melanie, Oishi, Meeko.
Subjects/Keywords: Path Planning; Uncertainty; Stochastic Reachability; Reinforcement Learning; Modeling Error
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APA (6th Edition):
Malone, N. D. (2015). High-Dimensional Motion Planning and Learning Under Uncertain Conditions. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/31730
Chicago Manual of Style (16th Edition):
Malone, Nick D. “High-Dimensional Motion Planning and Learning Under Uncertain Conditions.” 2015. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/31730.
MLA Handbook (7th Edition):
Malone, Nick D. “High-Dimensional Motion Planning and Learning Under Uncertain Conditions.” 2015. Web. 18 Jul 2019.
Vancouver:
Malone ND. High-Dimensional Motion Planning and Learning Under Uncertain Conditions. [Internet] [Doctoral dissertation]. University of New Mexico; 2015. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/31730.
Council of Science Editors:
Malone ND. High-Dimensional Motion Planning and Learning Under Uncertain Conditions. [Doctoral Dissertation]. University of New Mexico; 2015. Available from: http://hdl.handle.net/1928/31730
University of New Mexico
26.
Banerjee, Soumya.
Scaling in the immune system.
Degree: Department of Computer Science, 2013, University of New Mexico
URL: http://hdl.handle.net/1928/23083
► How different is the immune system in a human from that of a mouse? Do pathogens replicate at the same rate in different species? Answers…
(more)
▼ How different is the immune system in a human from that of a mouse? Do pathogens replicate at the same rate in different species? Answers to these questions have impact on human health since multi-host pathogens that jump from animals to humans affect millions worldwide. It is not known how rates of immune response and viral dynamics vary from species to species and how they depend on species body size. Metabolic scaling theory predicts that intracellular processes are slower in larger animals since cellular metabolic rates are slower. We test how rates of pathogenesis and immune system response rates depend on species body size. We hypothesize that immune response rates are invariant with body size. Our work suggests how the physical architecture of the immune system and chemical signals within it may lead to nearly scale-invariant immune search and response. We fit mathematical models to experimental West Nile Virus (WNV, a multi-host pathogen) infection data and investigate how model parameters characterizing the pathogen and the immune response change with respect to animal mass. Phylogeny also affects pathogenesis and immune response. We use a hierarchical Bayesian model, that incorporates phylogeny, to test hypotheses about the role of mass and phylogeny on pathogen replication and immune response. We observe that: 1) Hierarchical models (informed by phylogeny) make more accurate predictions of experimental data and more realistic estimates of biologically relevant parameters characterizing WNV infection. 2) Rates of WNV production decline with species body mass, modified by a phylogenetic influence. Our work is the first to systematically explore the role of host body mass in pathogenesis using mathematical models and empirical data. We investigate the complex interplay between the physical structure of the immune system and host body mass in determining immune response. The modeling strategies and tools outlined here are likely to be applicable to modeling of other multi-host pathogens. This work could also be extended to understand how drug and vaccine efficacy differ in humans from model organisms like mice where most immunological experiments are conducted.
Advisors/Committee Members: Moses, Melanie, Forrest, Stephanie, Perelson, Alan, Koster, Frederick, Lane, Terran.
Subjects/Keywords: scaling; immune system; mathematical modeling; viral dynamics; lymph node scaling
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APA (6th Edition):
Banerjee, S. (2013). Scaling in the immune system. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/23083
Chicago Manual of Style (16th Edition):
Banerjee, Soumya. “Scaling in the immune system.” 2013. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/23083.
MLA Handbook (7th Edition):
Banerjee, Soumya. “Scaling in the immune system.” 2013. Web. 18 Jul 2019.
Vancouver:
Banerjee S. Scaling in the immune system. [Internet] [Doctoral dissertation]. University of New Mexico; 2013. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/23083.
Council of Science Editors:
Banerjee S. Scaling in the immune system. [Doctoral Dissertation]. University of New Mexico; 2013. Available from: http://hdl.handle.net/1928/23083
University of New Mexico
27.
Hecker, Joshua Peter.
Evolving Efficient Foraging Behavior in Biologically-Inspired Robot Swarms.
Degree: Department of Computer Science, 2015, University of New Mexico
URL: http://hdl.handle.net/1928/31723
► Human beings are driven to explore distant new worlds as we seek to better understand our place in the Universe. Because of the inherent dangers…
(more)
▼ Human beings are driven to explore distant
new worlds as we seek to better understand our place in the Universe. Because of the inherent dangers of human spaceflight, we often send robots as surrogate explorers, controlled from millions of miles away by teams of capable rover drivers here on Earth. As technology continues to advance, scientists and engineers aspire to build low-cost, durable, fully autonomous rovers to succeed today's tele-operated extraplanetary explorers. Here we aim to advance this goal by designing and programming robots that can successfully navigate unknown and variable environments. We present a swarm robotics system that mimics the foraging behaviors of seed-harvester ants, employing evolutionary computation and machine learning to mitigate the adverse effects of unreliable information, variable environments, congestion bottlenecks, and sparse resources. We describe a central-place foraging algorithm (CPFA) whose parameters are evolved by a genetic algorithm (GA) to maximize foraging performance under different experimental conditions. We find that foraging for resources in heterogeneous clusters requires more complex communication, memory, and environmental sensing than strategies evolved in previous work. Additionally, we observe sub-linear scaling in resources collected per robot as swarm size increases, which we attribute to the 'bottleneck' constraint imposed by central-place foraging. Finally, we augment our foraging robot swarm with machine learning and statistical models, demonstrating that combining our existing biologically-inspired CPFA with a cluster exploitation algorithm produces more efficient total resource collection compared to each algorithm acting alone. While our system is designed to be a demonstration platform for swarm robotics research, this work provides a foundation for designing and implementing autonomous robot swarms that can function outside of the academic research laboratory. The ability of robot swarms to tolerate sensor noise, adapt to variable environments, distribute work across large teams, and identify and exploit heterogeneously-distributed resources are all critical factors for successful remote exploration missions on distant worlds.
Advisors/Committee Members: Moses, Melanie E., Tapia, Lydia, Fierro, Rafael, Winfield, Alan F.T..
Subjects/Keywords: Swarm robotics; Biologically-inspired computation; Central-place foraging; Genetic algorithms; Agent-based models
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APA (6th Edition):
Hecker, J. P. (2015). Evolving Efficient Foraging Behavior in Biologically-Inspired Robot Swarms. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/31723
Chicago Manual of Style (16th Edition):
Hecker, Joshua Peter. “Evolving Efficient Foraging Behavior in Biologically-Inspired Robot Swarms.” 2015. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/31723.
MLA Handbook (7th Edition):
Hecker, Joshua Peter. “Evolving Efficient Foraging Behavior in Biologically-Inspired Robot Swarms.” 2015. Web. 18 Jul 2019.
Vancouver:
Hecker JP. Evolving Efficient Foraging Behavior in Biologically-Inspired Robot Swarms. [Internet] [Doctoral dissertation]. University of New Mexico; 2015. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/31723.
Council of Science Editors:
Hecker JP. Evolving Efficient Foraging Behavior in Biologically-Inspired Robot Swarms. [Doctoral Dissertation]. University of New Mexico; 2015. Available from: http://hdl.handle.net/1928/31723
University of New Mexico
28.
Gunning, Christian E.
Population and Metapopulation Ecology of Childhood Diseases.
Degree: UNM Biology Department, 2014, University of New Mexico
URL: https://digitalrepository.unm.edu/biol_etds/46
► Researchers have long used mathematical models and empirical data to explore the population ecology of childhood diseases such as measles and whooping cough. These diseases…
(more)
▼ Researchers have long used mathematical models and empirical data to explore the population ecology of childhood diseases such as measles and whooping cough. These diseases have proven ideal model systems for studying population dynamics over space and time. Here we present a novel dataset of weekly measles and whooping cough case reports in pre-vaccine era U.S. cities and states, along with a previously- studied dataset of measles in England & Wales. We first estimate per-population disease reporting probabilities. We find that disease reporting is highly variable over space and between diseases, and correlated with socioeconomic covariates including ethnic composition and school attendance. Using these reporting estimates, we infer the long-term, marginal distribution of disease incidence for each population. This describes a probabilistic measure of disease persistence that compares favorably with a classic threshold persistence measure, critical community size (CCS). The U.S. and England & Wales exhibit similar patterns of measles incidence distributions: larger populations show higher mean viincidence and lower variance. The per-time probability of local extinction (conditioned on population size) is higher in the U.S. than in England & Wales, likely due to larger distances between U.S. cities. Finally, we use observed persistence and inferred incidence distributions to estimate the per-time probability of true persistence. Estimated persistence of whooping cough is much higher than persistence of measles (conditioned on population size). We find that cryptic persistence (the difference between observed and estimated persistence) of whooping cough is most common in small populations, while for measles cryptic persistence is most common in medium-sized populations that hover at the edge of extinction. Our results show that variation in disease reporting can significantly affect meta- population estimates of disease persistence, such as CCS. The distributional estimates of incidence presented here explicitly account for incomplete reporting, providing summaries of long-term ecological patterns that are comparable between metapopulations. These measures can provide disease control programs with valuable information on where disease incidence is expected to be higher or lower than expected based on population size alone.
Advisors/Committee Members: Wearing, Helen J., Erhardt, Erik B., Moses, Melanie E., Brown, James H..
Subjects/Keywords: population ecology; persistence; extinction; measles; pertussis; dynamical systems; stochastic; metapopulation; disease
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APA ·
Chicago ·
MLA ·
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CSE |
Export
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APA (6th Edition):
Gunning, C. E. (2014). Population and Metapopulation Ecology of Childhood Diseases. (Doctoral Dissertation). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/biol_etds/46
Chicago Manual of Style (16th Edition):
Gunning, Christian E. “Population and Metapopulation Ecology of Childhood Diseases.” 2014. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
https://digitalrepository.unm.edu/biol_etds/46.
MLA Handbook (7th Edition):
Gunning, Christian E. “Population and Metapopulation Ecology of Childhood Diseases.” 2014. Web. 18 Jul 2019.
Vancouver:
Gunning CE. Population and Metapopulation Ecology of Childhood Diseases. [Internet] [Doctoral dissertation]. University of New Mexico; 2014. [cited 2019 Jul 18].
Available from: https://digitalrepository.unm.edu/biol_etds/46.
Council of Science Editors:
Gunning CE. Population and Metapopulation Ecology of Childhood Diseases. [Doctoral Dissertation]. University of New Mexico; 2014. Available from: https://digitalrepository.unm.edu/biol_etds/46
29.
Semenov, Oleg.
Abstract Models of Molecular Walkers.
Degree: Department of Computer Science, 2013, University of New Mexico
URL: http://hdl.handle.net/1928/23579
► Recent advances in single-molecule chemistry have led to designs for artificial multi-pedal walkers that follow tracks of chemicals. The walkers, called molecular spiders, consist of…
(more)
▼ Recent advances in single-molecule chemistry have led to designs for artificial multi-pedal walkers that follow tracks of chemicals. The walkers, called molecular spiders, consist of a rigid chemically inert body and several flexible enzymatic legs. The legs can reversibly bind to chemical substrates on a surface, and through their enzymatic action convert them to products. We study abstract models of molecular spiders to evaluate how efficiently they can perform two tasks: molecular transport of cargo over tracks and search for targets on finite surfaces. For the single-spider model our simulations show a transient behavior wherein certain spiders move superdiffusively over significant distances and times. This gives the spiders potential as a faster-than-diffusion transport mechanism. However, analysis shows that single-spider motion eventually decays into an ordinary diffusive motion, owing to the ever increasing size of the region of products. Inspired by cooperative behavior of natural molecular walkers, we propose a symmetric exclusion process (SEP) model for multiple walkers interacting as they move over a one-dimensional lattice. We show that when walkers are sequentially released from the origin, the collective effect is to prevent the leading walkers from moving too far backwards. Hence, there is an effective outward pressure on the leading walkers that keeps them moving superdiffusively for longer times. Despite this improvement the leading spider eventually slows down and moves diffusively, similarly to a single spider. The slowdown happens because all spiders behind the leading spiders never encounter substrates, and thus they are never biased. They cannot keep up with leading spiders, and cannot put enough pressure on them. Next, we investigate search properties of a single and multiple spiders moving over one- and two-dimensional surfaces with various absorbing and reflecting boundaries. For the single-spider model we evaluate by how much the slowdown on newly visited sites, owing to catalysis, can improve the mean first passage time of spiders and show that in one dimension, when both ends of the track are an absorbing boundary, the performance gain is lower than in two dimensions, when the absorbing boundary is a circle; this persists even when the absorbing boundary is a single site. Next, we study how multiple molecular spiders influence one another during the search. We show that when one spider reaches the trace of another spider it is more likely not to follow the trace and instead explore unvisited sites. This interaction between the spiders gives them an advantage over independent random walkers in a search for multiple targets. We also study how efficiently the spiders with various gaits are able to find specific targets. Spiders with gaits that allow more freedom of leg movement find their targets faster than spiders with more restrictive gaits. For every gait, there is an optimal detachment rate that minimizes the time to find all target sites.
Advisors/Committee Members: Stefanovic, Darko, Moore, Cristopher, Moses, Melanie, Stojanovic, Milan N., Krapivsky, Pavel L..
Subjects/Keywords: Molecular Motors; Simulation; Kinetic Monte Carlo
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
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Manager
APA (6th Edition):
Semenov, O. (2013). Abstract Models of Molecular Walkers. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/23579
Chicago Manual of Style (16th Edition):
Semenov, Oleg. “Abstract Models of Molecular Walkers.” 2013. Doctoral Dissertation, University of New Mexico. Accessed July 18, 2019.
http://hdl.handle.net/1928/23579.
MLA Handbook (7th Edition):
Semenov, Oleg. “Abstract Models of Molecular Walkers.” 2013. Web. 18 Jul 2019.
Vancouver:
Semenov O. Abstract Models of Molecular Walkers. [Internet] [Doctoral dissertation]. University of New Mexico; 2013. [cited 2019 Jul 18].
Available from: http://hdl.handle.net/1928/23579.
Council of Science Editors:
Semenov O. Abstract Models of Molecular Walkers. [Doctoral Dissertation]. University of New Mexico; 2013. Available from: http://hdl.handle.net/1928/23579
. 
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