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You searched for +publisher:"University of Georgia" +contributor:("Prashant Doshi"). Showing records 1 – 21 of 21 total matches.

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University of Georgia

1. Kolli, Ravikanth. Scalable matching of ontology graphs using partitioning.

Degree: MS, Computer Science, 2008, University of Georgia

 The problem of ontology matching is crucial due to decentralized development and publication ofontological data. An approach proposed towards matching the ontologies is by inferring… (more)

Subjects/Keywords: Ontologies

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APA (6th Edition):

Kolli, R. (2008). Scalable matching of ontology graphs using partitioning. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/kolli_ravikanth_200808_ms

Chicago Manual of Style (16th Edition):

Kolli, Ravikanth. “Scalable matching of ontology graphs using partitioning.” 2008. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/kolli_ravikanth_200808_ms.

MLA Handbook (7th Edition):

Kolli, Ravikanth. “Scalable matching of ontology graphs using partitioning.” 2008. Web. 25 Apr 2019.

Vancouver:

Kolli R. Scalable matching of ontology graphs using partitioning. [Internet] [Masters thesis]. University of Georgia; 2008. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/kolli_ravikanth_200808_ms.

Council of Science Editors:

Kolli R. Scalable matching of ontology graphs using partitioning. [Masters Thesis]. University of Georgia; 2008. Available from: http://purl.galileo.usg.edu/uga_etd/kolli_ravikanth_200808_ms


University of Georgia

2. Zhao, Haibo. Scalable composition of Web services under uncertainty.

Degree: PhD, Computer Science, 2009, University of Georgia

 Facilitating the assembly of services to form composite services is an important functionality in Service-oriented architecture (SOA). In this dissertation, we focus on the problem… (more)

Subjects/Keywords: Web service composition

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APA (6th Edition):

Zhao, H. (2009). Scalable composition of Web services under uncertainty. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/zhao_haibo_200908_phd

Chicago Manual of Style (16th Edition):

Zhao, Haibo. “Scalable composition of Web services under uncertainty.” 2009. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/zhao_haibo_200908_phd.

MLA Handbook (7th Edition):

Zhao, Haibo. “Scalable composition of Web services under uncertainty.” 2009. Web. 25 Apr 2019.

Vancouver:

Zhao H. Scalable composition of Web services under uncertainty. [Internet] [Doctoral dissertation]. University of Georgia; 2009. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/zhao_haibo_200908_phd.

Council of Science Editors:

Zhao H. Scalable composition of Web services under uncertainty. [Doctoral Dissertation]. University of Georgia; 2009. Available from: http://purl.galileo.usg.edu/uga_etd/zhao_haibo_200908_phd


University of Georgia

3. Paradesi, Sharon Myrtle. Integrating behavioral trust and reputation in Web service compositions.

Degree: MS, Computer Science, 2009, University of Georgia

 Algorithms for composing Web services traditionally utilize the functional and quality-of-service parameters of candidate services to decide which services to include in the composition. Users… (more)

Subjects/Keywords: Trust

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APA (6th Edition):

Paradesi, S. M. (2009). Integrating behavioral trust and reputation in Web service compositions. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/paradesi_sharon_m_200912_ms

Chicago Manual of Style (16th Edition):

Paradesi, Sharon Myrtle. “Integrating behavioral trust and reputation in Web service compositions.” 2009. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/paradesi_sharon_m_200912_ms.

MLA Handbook (7th Edition):

Paradesi, Sharon Myrtle. “Integrating behavioral trust and reputation in Web service compositions.” 2009. Web. 25 Apr 2019.

Vancouver:

Paradesi SM. Integrating behavioral trust and reputation in Web service compositions. [Internet] [Masters thesis]. University of Georgia; 2009. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/paradesi_sharon_m_200912_ms.

Council of Science Editors:

Paradesi SM. Integrating behavioral trust and reputation in Web service compositions. [Masters Thesis]. University of Georgia; 2009. Available from: http://purl.galileo.usg.edu/uga_etd/paradesi_sharon_m_200912_ms


University of Georgia

4. Chandrasekaran, Muthukumaran. Approximate model equivalence for interactive dynamic influence diagrams.

Degree: MS, Artificial Intelligence, 2010, University of Georgia

 Interactive dynamic influence diagrams (I-DIDs) graphically visualize a sequential decision problem for uncertain settings where multiple agents interact not only amongst themselves but also with… (more)

Subjects/Keywords: Distributed Artificial Intelligence

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APA (6th Edition):

Chandrasekaran, M. (2010). Approximate model equivalence for interactive dynamic influence diagrams. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/chandrasekaran_muthukumaran_201005_ms

Chicago Manual of Style (16th Edition):

Chandrasekaran, Muthukumaran. “Approximate model equivalence for interactive dynamic influence diagrams.” 2010. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/chandrasekaran_muthukumaran_201005_ms.

MLA Handbook (7th Edition):

Chandrasekaran, Muthukumaran. “Approximate model equivalence for interactive dynamic influence diagrams.” 2010. Web. 25 Apr 2019.

Vancouver:

Chandrasekaran M. Approximate model equivalence for interactive dynamic influence diagrams. [Internet] [Masters thesis]. University of Georgia; 2010. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/chandrasekaran_muthukumaran_201005_ms.

Council of Science Editors:

Chandrasekaran M. Approximate model equivalence for interactive dynamic influence diagrams. [Masters Thesis]. University of Georgia; 2010. Available from: http://purl.galileo.usg.edu/uga_etd/chandrasekaran_muthukumaran_201005_ms


University of Georgia

5. Harney, John. Selective querying for adapting Web service compositions using the value of changed information.

Degree: PhD, Computer Science, 2010, University of Georgia

 Web services are autonomous, reusable, platform-independent software applications that can be accessed over the Web. One of the key advantages of utilizing Web services is… (more)

Subjects/Keywords: Value of Information; Modeling; Services-Oriented Computing; Web Services; Web Services Compositions; Adaptation; Theses

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APA (6th Edition):

Harney, J. (2010). Selective querying for adapting Web service compositions using the value of changed information. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/harney_john_201008_phd

Chicago Manual of Style (16th Edition):

Harney, John. “Selective querying for adapting Web service compositions using the value of changed information.” 2010. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/harney_john_201008_phd.

MLA Handbook (7th Edition):

Harney, John. “Selective querying for adapting Web service compositions using the value of changed information.” 2010. Web. 25 Apr 2019.

Vancouver:

Harney J. Selective querying for adapting Web service compositions using the value of changed information. [Internet] [Doctoral dissertation]. University of Georgia; 2010. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/harney_john_201008_phd.

Council of Science Editors:

Harney J. Selective querying for adapting Web service compositions using the value of changed information. [Doctoral Dissertation]. University of Georgia; 2010. Available from: http://purl.galileo.usg.edu/uga_etd/harney_john_201008_phd


University of Georgia

6. Vembu, Nithya. A translator Web service for data mediation in Web service compositions.

Degree: MS, Artificial Intelligence, 2011, University of Georgia

 Atomic Web services may not always provide solutions for business requests. In such cases, several services are integrated to create new composite services with added… (more)

Subjects/Keywords: Web Service Composition

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APA (6th Edition):

Vembu, N. (2011). A translator Web service for data mediation in Web service compositions. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/vembu_nithya_201105_ms

Chicago Manual of Style (16th Edition):

Vembu, Nithya. “A translator Web service for data mediation in Web service compositions.” 2011. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/vembu_nithya_201105_ms.

MLA Handbook (7th Edition):

Vembu, Nithya. “A translator Web service for data mediation in Web service compositions.” 2011. Web. 25 Apr 2019.

Vancouver:

Vembu N. A translator Web service for data mediation in Web service compositions. [Internet] [Masters thesis]. University of Georgia; 2011. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/vembu_nithya_201105_ms.

Council of Science Editors:

Vembu N. A translator Web service for data mediation in Web service compositions. [Masters Thesis]. University of Georgia; 2011. Available from: http://purl.galileo.usg.edu/uga_etd/vembu_nithya_201105_ms


University of Georgia

7. Qu, Xia. Strategic behavior under uncertainty in multiagent settings.

Degree: PhD, Computer Science, 2014, University of Georgia

 Sequential decision making under uncertainty involves selecting a sequence of actions in the presence of noise to maximize an agent's expected utility. In multiagent settings,… (more)

Subjects/Keywords: Human behavor modeling

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APA (6th Edition):

Qu, X. (2014). Strategic behavior under uncertainty in multiagent settings. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/qu_xia_201408_phd

Chicago Manual of Style (16th Edition):

Qu, Xia. “Strategic behavior under uncertainty in multiagent settings.” 2014. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/qu_xia_201408_phd.

MLA Handbook (7th Edition):

Qu, Xia. “Strategic behavior under uncertainty in multiagent settings.” 2014. Web. 25 Apr 2019.

Vancouver:

Qu X. Strategic behavior under uncertainty in multiagent settings. [Internet] [Doctoral dissertation]. University of Georgia; 2014. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/qu_xia_201408_phd.

Council of Science Editors:

Qu X. Strategic behavior under uncertainty in multiagent settings. [Doctoral Dissertation]. University of Georgia; 2014. Available from: http://purl.galileo.usg.edu/uga_etd/qu_xia_201408_phd


University of Georgia

8. Sonu, Ekhlas Shaikh. Scalable algorithms for sequential decision making under uncertainty in multiagent systems.

Degree: PhD, Computer Science, 2015, University of Georgia

 Decision making or planning is a crucial part of AI research. In recent times, deploying autonomous agents – such as search and rescue robots, autonomous… (more)

Subjects/Keywords: Artificial intelligence

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APA (6th Edition):

Sonu, E. S. (2015). Scalable algorithms for sequential decision making under uncertainty in multiagent systems. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/sonu_ekhlas_s_201508_phd

Chicago Manual of Style (16th Edition):

Sonu, Ekhlas Shaikh. “Scalable algorithms for sequential decision making under uncertainty in multiagent systems.” 2015. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/sonu_ekhlas_s_201508_phd.

MLA Handbook (7th Edition):

Sonu, Ekhlas Shaikh. “Scalable algorithms for sequential decision making under uncertainty in multiagent systems.” 2015. Web. 25 Apr 2019.

Vancouver:

Sonu ES. Scalable algorithms for sequential decision making under uncertainty in multiagent systems. [Internet] [Doctoral dissertation]. University of Georgia; 2015. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/sonu_ekhlas_s_201508_phd.

Council of Science Editors:

Sonu ES. Scalable algorithms for sequential decision making under uncertainty in multiagent systems. [Doctoral Dissertation]. University of Georgia; 2015. Available from: http://purl.galileo.usg.edu/uga_etd/sonu_ekhlas_s_201508_phd


University of Georgia

9. Perez Barrenechea, Dennis David. Anytime point based approximations for interactive POMDPs.

Degree: MS, Artificial Intelligence, 2007, University of Georgia

 Partially observable Markov decision processes (POMDPs) have been largely accepted as a rich-framework for planning and control problems. In settings where multiple agents interact, POMDPs… (more)

Subjects/Keywords: Markov Decision Process

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APA (6th Edition):

Perez Barrenechea, D. D. (2007). Anytime point based approximations for interactive POMDPs. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/perez-barrenechea_dennis_d_200712_ms

Chicago Manual of Style (16th Edition):

Perez Barrenechea, Dennis David. “Anytime point based approximations for interactive POMDPs.” 2007. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/perez-barrenechea_dennis_d_200712_ms.

MLA Handbook (7th Edition):

Perez Barrenechea, Dennis David. “Anytime point based approximations for interactive POMDPs.” 2007. Web. 25 Apr 2019.

Vancouver:

Perez Barrenechea DD. Anytime point based approximations for interactive POMDPs. [Internet] [Masters thesis]. University of Georgia; 2007. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/perez-barrenechea_dennis_d_200712_ms.

Council of Science Editors:

Perez Barrenechea DD. Anytime point based approximations for interactive POMDPs. [Masters Thesis]. University of Georgia; 2007. Available from: http://purl.galileo.usg.edu/uga_etd/perez-barrenechea_dennis_d_200712_ms


University of Georgia

10. Bogert, Kenneth Daniel. Inverse reinforcement learning for robotic applications: hidden variables, multiple experts and unknown dynamics.

Degree: PhD, Computer Science, 2016, University of Georgia

 Robots deployed into many real-world scenarios are expected to face situations that their designers could not anticipate. Machine learning is an effective tool for extending… (more)

Subjects/Keywords: robotics

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APA (6th Edition):

Bogert, K. D. (2016). Inverse reinforcement learning for robotic applications: hidden variables, multiple experts and unknown dynamics. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/bogert_kenneth_d_201608_phd

Chicago Manual of Style (16th Edition):

Bogert, Kenneth Daniel. “Inverse reinforcement learning for robotic applications: hidden variables, multiple experts and unknown dynamics.” 2016. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/bogert_kenneth_d_201608_phd.

MLA Handbook (7th Edition):

Bogert, Kenneth Daniel. “Inverse reinforcement learning for robotic applications: hidden variables, multiple experts and unknown dynamics.” 2016. Web. 25 Apr 2019.

Vancouver:

Bogert KD. Inverse reinforcement learning for robotic applications: hidden variables, multiple experts and unknown dynamics. [Internet] [Doctoral dissertation]. University of Georgia; 2016. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/bogert_kenneth_d_201608_phd.

Council of Science Editors:

Bogert KD. Inverse reinforcement learning for robotic applications: hidden variables, multiple experts and unknown dynamics. [Doctoral Dissertation]. University of Georgia; 2016. Available from: http://purl.galileo.usg.edu/uga_etd/bogert_kenneth_d_201608_phd


University of Georgia

11. Bhat, Sanath Govinda. Learning driver preferences for freeway merging using multitask irl.

Degree: MS, Computer Science, 2017, University of Georgia

 Most automobile manufacturers today have invested heavily in the research and design of implementing autonomy in their cars. One important and challenging problem faced by… (more)

Subjects/Keywords: Inverse Reinforcement Learning; Hierarchical Bayesian Model; Multitask; Highway Merging; NGSIM; Likelihood Weighting

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APA (6th Edition):

Bhat, S. G. (2017). Learning driver preferences for freeway merging using multitask irl. (Masters Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/37273

Chicago Manual of Style (16th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://hdl.handle.net/10724/37273.

MLA Handbook (7th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Web. 25 Apr 2019.

Vancouver:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Internet] [Masters thesis]. University of Georgia; 2017. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/10724/37273.

Council of Science Editors:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Masters Thesis]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/37273


University of Georgia

12. Chandrasekaran, Muthukumaran. Frameworks and algorithms for individual planning under cooperation.

Degree: PhD, Computer Science, 2017, University of Georgia

 Interactive Dynamic Influence Diagrams (I-DIDs) and Interactive Partially Observable Markov Decision Processes (I-POMDPs) are well-established finitely-nested frameworks that operationalize the planning and decision-making of a… (more)

Subjects/Keywords: multiagent systems; graphical models; bisimulation; reinforcement learning; markov decision processes; teamwork; ad hoc teams; game theory; open agent systems

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APA (6th Edition):

Chandrasekaran, M. (2017). Frameworks and algorithms for individual planning under cooperation. (Doctoral Dissertation). University of Georgia. Retrieved from http://hdl.handle.net/10724/37284

Chicago Manual of Style (16th Edition):

Chandrasekaran, Muthukumaran. “Frameworks and algorithms for individual planning under cooperation.” 2017. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://hdl.handle.net/10724/37284.

MLA Handbook (7th Edition):

Chandrasekaran, Muthukumaran. “Frameworks and algorithms for individual planning under cooperation.” 2017. Web. 25 Apr 2019.

Vancouver:

Chandrasekaran M. Frameworks and algorithms for individual planning under cooperation. [Internet] [Doctoral dissertation]. University of Georgia; 2017. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/10724/37284.

Council of Science Editors:

Chandrasekaran M. Frameworks and algorithms for individual planning under cooperation. [Doctoral Dissertation]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/37284


University of Georgia

13. Chandrasekaran, Muthukumaran. Frameworks and algorithms for individual planning under cooperation.

Degree: PhD, Computer Science, 2017, University of Georgia

 Interactive Dynamic Influence Diagrams (I-DIDs) and Interactive Partially Observable Markov Decision Processes (I-POMDPs) are well-established finitely-nested frameworks that operationalize the planning and decision-making of a… (more)

Subjects/Keywords: multiagent systems; graphical models; bisimulation; reinforcement learning; markov decision processes; teamwork; ad hoc teams; game theory; open agent systems

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APA (6th Edition):

Chandrasekaran, M. (2017). Frameworks and algorithms for individual planning under cooperation. (Doctoral Dissertation). University of Georgia. Retrieved from http://hdl.handle.net/10724/37127

Chicago Manual of Style (16th Edition):

Chandrasekaran, Muthukumaran. “Frameworks and algorithms for individual planning under cooperation.” 2017. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://hdl.handle.net/10724/37127.

MLA Handbook (7th Edition):

Chandrasekaran, Muthukumaran. “Frameworks and algorithms for individual planning under cooperation.” 2017. Web. 25 Apr 2019.

Vancouver:

Chandrasekaran M. Frameworks and algorithms for individual planning under cooperation. [Internet] [Doctoral dissertation]. University of Georgia; 2017. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/10724/37127.

Council of Science Editors:

Chandrasekaran M. Frameworks and algorithms for individual planning under cooperation. [Doctoral Dissertation]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/37127


University of Georgia

14. Bhat, Sanath Govinda. Learning driver preferences for freeway merging using multitask irl.

Degree: MS, Computer Science, 2017, University of Georgia

 Most automobile manufacturers today have invested heavily in the research and design of implementing autonomy in their cars. One important and challenging problem faced by… (more)

Subjects/Keywords: Inverse Reinforcement Learning; Hierarchical Bayesian Model; Multitask; Highway Merging; NGSIM; Likelihood Weighting

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APA (6th Edition):

Bhat, S. G. (2017). Learning driver preferences for freeway merging using multitask irl. (Masters Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/37116

Chicago Manual of Style (16th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://hdl.handle.net/10724/37116.

MLA Handbook (7th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Web. 25 Apr 2019.

Vancouver:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Internet] [Masters thesis]. University of Georgia; 2017. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/10724/37116.

Council of Science Editors:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Masters Thesis]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/37116

15. Das, Indrajit. Inverse reinforcement learning of risk-sensitive utility.

Degree: MS, Computer Science, 2016, University of Georgia

 The uncertain and stochastic nature of the real world poses a challenge for autonomous cars in making decisions to ensure appropriate motion, considering the safety… (more)

Subjects/Keywords: Inverse Reinforcement Learning

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APA (6th Edition):

Das, I. (2016). Inverse reinforcement learning of risk-sensitive utility. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/das_indrajit_201608_ms

Chicago Manual of Style (16th Edition):

Das, Indrajit. “Inverse reinforcement learning of risk-sensitive utility.” 2016. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/das_indrajit_201608_ms.

MLA Handbook (7th Edition):

Das, Indrajit. “Inverse reinforcement learning of risk-sensitive utility.” 2016. Web. 25 Apr 2019.

Vancouver:

Das I. Inverse reinforcement learning of risk-sensitive utility. [Internet] [Masters thesis]. University of Georgia; 2016. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/das_indrajit_201608_ms.

Council of Science Editors:

Das I. Inverse reinforcement learning of risk-sensitive utility. [Masters Thesis]. University of Georgia; 2016. Available from: http://purl.galileo.usg.edu/uga_etd/das_indrajit_201608_ms

16. Asiaee, Amir Hosein. A framework for ontology-based question answering with application to parasite data.

Degree: PhD, Computer Science, 2013, University of Georgia

 Research in life sciences requires a sophisticated and integrated platform to query and analyze a large volume of data represented in various data. Two major… (more)

Subjects/Keywords: Question Answering

…the Center for Tropical and Emerging Global Disease at the University of Georgia. The main… 

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APA (6th Edition):

Asiaee, A. H. (2013). A framework for ontology-based question answering with application to parasite data. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/asiaee_amir_h_201312_phd

Chicago Manual of Style (16th Edition):

Asiaee, Amir Hosein. “A framework for ontology-based question answering with application to parasite data.” 2013. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/asiaee_amir_h_201312_phd.

MLA Handbook (7th Edition):

Asiaee, Amir Hosein. “A framework for ontology-based question answering with application to parasite data.” 2013. Web. 25 Apr 2019.

Vancouver:

Asiaee AH. A framework for ontology-based question answering with application to parasite data. [Internet] [Doctoral dissertation]. University of Georgia; 2013. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/asiaee_amir_h_201312_phd.

Council of Science Editors:

Asiaee AH. A framework for ontology-based question answering with application to parasite data. [Doctoral Dissertation]. University of Georgia; 2013. Available from: http://purl.galileo.usg.edu/uga_etd/asiaee_amir_h_201312_phd

17. Chaudhari, Tejas Dattatray. Complex concept matching for improved ontology alignment.

Degree: MS, Computer Science, 2012, University of Georgia

 Modern ontology languages such as Web Ontology Language (OWL) allow defining complex concepts using restrictions, Boolean combinations, and exhaustive enumeration of instances. As ontology repositories… (more)

Subjects/Keywords: Alignment

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APA (6th Edition):

Chaudhari, T. D. (2012). Complex concept matching for improved ontology alignment. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/chaudhari_tejas_d_201212_ms

Chicago Manual of Style (16th Edition):

Chaudhari, Tejas Dattatray. “Complex concept matching for improved ontology alignment.” 2012. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/chaudhari_tejas_d_201212_ms.

MLA Handbook (7th Edition):

Chaudhari, Tejas Dattatray. “Complex concept matching for improved ontology alignment.” 2012. Web. 25 Apr 2019.

Vancouver:

Chaudhari TD. Complex concept matching for improved ontology alignment. [Internet] [Masters thesis]. University of Georgia; 2012. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/chaudhari_tejas_d_201212_ms.

Council of Science Editors:

Chaudhari TD. Complex concept matching for improved ontology alignment. [Masters Thesis]. University of Georgia; 2012. Available from: http://purl.galileo.usg.edu/uga_etd/chaudhari_tejas_d_201212_ms

18. Trivedi, Maulesh. Inverse learning of robot behavior for ad-hoc teamwork.

Degree: MS, Artificial Intelligence, 2016, University of Georgia

 Machine Learning and Robotics present a very intriguing combination of research in Artificial Intelligence. Inverse Reinforcement Learning (IRL) algorithms have generated a great deal of… (more)

Subjects/Keywords: Inverse Reinforcement Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Trivedi, M. (2016). Inverse learning of robot behavior for ad-hoc teamwork. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/trivedi_maulesh_201608_ms

Chicago Manual of Style (16th Edition):

Trivedi, Maulesh. “Inverse learning of robot behavior for ad-hoc teamwork.” 2016. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/trivedi_maulesh_201608_ms.

MLA Handbook (7th Edition):

Trivedi, Maulesh. “Inverse learning of robot behavior for ad-hoc teamwork.” 2016. Web. 25 Apr 2019.

Vancouver:

Trivedi M. Inverse learning of robot behavior for ad-hoc teamwork. [Internet] [Masters thesis]. University of Georgia; 2016. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/trivedi_maulesh_201608_ms.

Council of Science Editors:

Trivedi M. Inverse learning of robot behavior for ad-hoc teamwork. [Masters Thesis]. University of Georgia; 2016. Available from: http://purl.galileo.usg.edu/uga_etd/trivedi_maulesh_201608_ms

19. Mesbah , Anousha. Individual localization using landmarks in the presence of interacting robots.

Degree: MS, Computer Science, 2012, University of Georgia

 In order to path plan and navigate smoothly toward a goal, a mobile robot must know where it is in the environment. Thus robust state… (more)

Subjects/Keywords: Localization

…Center at the University of Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . 51 6.8… …environment on the 5th floor of Boyd GSRC at the University of Georgia. We demonstrate that by using… 

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APA (6th Edition):

Mesbah , A. (2012). Individual localization using landmarks in the presence of interacting robots. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/mesbah-_anousha_201205_ms

Chicago Manual of Style (16th Edition):

Mesbah , Anousha. “Individual localization using landmarks in the presence of interacting robots.” 2012. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/mesbah-_anousha_201205_ms.

MLA Handbook (7th Edition):

Mesbah , Anousha. “Individual localization using landmarks in the presence of interacting robots.” 2012. Web. 25 Apr 2019.

Vancouver:

Mesbah A. Individual localization using landmarks in the presence of interacting robots. [Internet] [Masters thesis]. University of Georgia; 2012. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/mesbah-_anousha_201205_ms.

Council of Science Editors:

Mesbah A. Individual localization using landmarks in the presence of interacting robots. [Masters Thesis]. University of Georgia; 2012. Available from: http://purl.galileo.usg.edu/uga_etd/mesbah-_anousha_201205_ms

20. Thayasivam, Uthayasanker. Algorithms for complete, efficient, and scalable alignment of large ontologies.

Degree: PhD, Computer Science, 2013, University of Georgia

 As ontology repositories proliferate on the web, many contain ontologies that overlap in scope. Ontology alignment (OA) is the process of identifying this overlap, which… (more)

Subjects/Keywords: Scalability

…here at THINC lab, Department of Computer Science, University of Georgia. It models… …of ontology alignment task. Jointly with my advisor Prof. Prashant Doshi, I have endeavored… …Uthayasanker Thayasivam, Prashant Doshi, “Improved Efficiency of Iterative Ontology Alignment using… …under review. 2. Uthayasanker Thayasivam, Prashant Doshi, “Speeding up Batch Alignment of… …ICSC) 2013. vi vii 3. Tejas Chaudhari, Uthayasanker Thayasivam, Prashant Doshi… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Thayasivam, U. (2013). Algorithms for complete, efficient, and scalable alignment of large ontologies. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/thayasivam_uthayasanker_201308_phd

Chicago Manual of Style (16th Edition):

Thayasivam, Uthayasanker. “Algorithms for complete, efficient, and scalable alignment of large ontologies.” 2013. Doctoral Dissertation, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/thayasivam_uthayasanker_201308_phd.

MLA Handbook (7th Edition):

Thayasivam, Uthayasanker. “Algorithms for complete, efficient, and scalable alignment of large ontologies.” 2013. Web. 25 Apr 2019.

Vancouver:

Thayasivam U. Algorithms for complete, efficient, and scalable alignment of large ontologies. [Internet] [Doctoral dissertation]. University of Georgia; 2013. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/thayasivam_uthayasanker_201308_phd.

Council of Science Editors:

Thayasivam U. Algorithms for complete, efficient, and scalable alignment of large ontologies. [Doctoral Dissertation]. University of Georgia; 2013. Available from: http://purl.galileo.usg.edu/uga_etd/thayasivam_uthayasanker_201308_phd

21. Marathe, Kedar Pramodan. An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion.

Degree: MS, Artificial Intelligence, 2014, University of Georgia

 Robot localization under extreme occlusion is a common scenario in the real world. Examples include an autonomous car following another car along long stretches of… (more)

Subjects/Keywords: Particle Filter

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Marathe, K. P. (2014). An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms

Chicago Manual of Style (16th Edition):

Marathe, Kedar Pramodan. “An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion.” 2014. Masters Thesis, University of Georgia. Accessed April 25, 2019. http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms.

MLA Handbook (7th Edition):

Marathe, Kedar Pramodan. “An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion.” 2014. Web. 25 Apr 2019.

Vancouver:

Marathe KP. An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion. [Internet] [Masters thesis]. University of Georgia; 2014. [cited 2019 Apr 25]. Available from: http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms.

Council of Science Editors:

Marathe KP. An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion. [Masters Thesis]. University of Georgia; 2014. Available from: http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms

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