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You searched for +publisher:"University of Texas – Austin" +contributor:("Miikkulainen, Risto"). Showing records 1 – 21 of 21 total matches.

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University of Texas – Austin

1. Bahceci, Erkin. Competitive multi-agent search.

Degree: PhD, Computer Science, 2014, University of Texas – Austin

 While evolutionary computation is well suited for automatic discovery in engineering, it can also be used to gain insight into how humans and organizations could… (more)

Subjects/Keywords: Competitive multi-agent search; Evolutionary computation; NK model; Neuroevolution of augmenting topologies; Compositional pattern-producing network

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APA (6th Edition):

Bahceci, E. (2014). Competitive multi-agent search. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/28368

Chicago Manual of Style (16th Edition):

Bahceci, Erkin. “Competitive multi-agent search.” 2014. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/28368.

MLA Handbook (7th Edition):

Bahceci, Erkin. “Competitive multi-agent search.” 2014. Web. 07 Aug 2020.

Vancouver:

Bahceci E. Competitive multi-agent search. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2014. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/28368.

Council of Science Editors:

Bahceci E. Competitive multi-agent search. [Doctoral Dissertation]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/28368


University of Texas – Austin

2. Waters, Austin Severn. Infinite-word topic models for digital media.

Degree: PhD, Computer Sciences, 2014, University of Texas – Austin

 Digital media collections hold an unprecedented source of knowledge and data about the world. Yet, even at current scales, the data exceeds by many orders… (more)

Subjects/Keywords: Machine learning; Topic models; Variational inference; Bayesian nonparametrics

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APA (6th Edition):

Waters, A. S. (2014). Infinite-word topic models for digital media. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/24968

Chicago Manual of Style (16th Edition):

Waters, Austin Severn. “Infinite-word topic models for digital media.” 2014. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/24968.

MLA Handbook (7th Edition):

Waters, Austin Severn. “Infinite-word topic models for digital media.” 2014. Web. 07 Aug 2020.

Vancouver:

Waters AS. Infinite-word topic models for digital media. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2014. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/24968.

Council of Science Editors:

Waters AS. Infinite-word topic models for digital media. [Doctoral Dissertation]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/24968


University of Texas – Austin

3. -7404-8707. Object-model transfer in the general video game domain.

Degree: MSin Computer Sciences, Computer Science, 2019, University of Texas – Austin

 Reinforcement learning agents often benefit from learning models that predict their environment. However, learned models may not generalize well to novel situations. This thesis investigates… (more)

Subjects/Keywords: Model learning; Reinforcement learning; Transfer learning; Video game playing

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APA (6th Edition):

-7404-8707. (2019). Object-model transfer in the general video game domain. (Masters Thesis). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/3139

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7404-8707. “Object-model transfer in the general video game domain.” 2019. Masters Thesis, University of Texas – Austin. Accessed August 07, 2020. http://dx.doi.org/10.26153/tsw/3139.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7404-8707. “Object-model transfer in the general video game domain.” 2019. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7404-8707. Object-model transfer in the general video game domain. [Internet] [Masters thesis]. University of Texas – Austin; 2019. [cited 2020 Aug 07]. Available from: http://dx.doi.org/10.26153/tsw/3139.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7404-8707. Object-model transfer in the general video game domain. [Masters Thesis]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/3139

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

4. -5021-9014. MDEA : malware detection with evolutionary adversarial learning.

Degree: MSin Computer Sciences, Computer Science, 2020, University of Texas – Austin

 Many applications have used machine learning as a tool to detect malware. These applications take in raw or processed binary data to feed neural network… (more)

Subjects/Keywords: Evolutionary algorithm; Malware detection

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APA (6th Edition):

-5021-9014. (2020). MDEA : malware detection with evolutionary adversarial learning. (Masters Thesis). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/7424

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-5021-9014. “MDEA : malware detection with evolutionary adversarial learning.” 2020. Masters Thesis, University of Texas – Austin. Accessed August 07, 2020. http://dx.doi.org/10.26153/tsw/7424.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-5021-9014. “MDEA : malware detection with evolutionary adversarial learning.” 2020. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5021-9014. MDEA : malware detection with evolutionary adversarial learning. [Internet] [Masters thesis]. University of Texas – Austin; 2020. [cited 2020 Aug 07]. Available from: http://dx.doi.org/10.26153/tsw/7424.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5021-9014. MDEA : malware detection with evolutionary adversarial learning. [Masters Thesis]. University of Texas – Austin; 2020. Available from: http://dx.doi.org/10.26153/tsw/7424

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

5. -7041-9136. Evolutionary bilevel optimization for complex control problems and blackbox function optimization.

Degree: MSin Computer Sciences, Computer Science, 2015, University of Texas – Austin

 Most optimization algorithms must undergo time consuming parameter tuning in order to solve complex, real-world control tasks. Parameter tuning is inherently a bilevel optimization problem:… (more)

Subjects/Keywords: Genetic algorithms; Metaheuristics; Neural networks; Fitness approximation; Parameter tuning

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APA (6th Edition):

-7041-9136. (2015). Evolutionary bilevel optimization for complex control problems and blackbox function optimization. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31848

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7041-9136. “Evolutionary bilevel optimization for complex control problems and blackbox function optimization.” 2015. Masters Thesis, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/31848.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7041-9136. “Evolutionary bilevel optimization for complex control problems and blackbox function optimization.” 2015. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7041-9136. Evolutionary bilevel optimization for complex control problems and blackbox function optimization. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/31848.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7041-9136. Evolutionary bilevel optimization for complex control problems and blackbox function optimization. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31848

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

6. -3115-1189. Fly with me : algorithms and methods for influencing a flock.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 As robots become more affordable, they will begin to exist in the world in greater quantities. Some of these robots will likely be designed to… (more)

Subjects/Keywords: Flocking; Ad hoc teamwork; Influencing a flock; Ad hoc agent; Multiagent teamwork; Swarms

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APA (6th Edition):

-3115-1189. (2017). Fly with me : algorithms and methods for influencing a flock. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61905

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-3115-1189. “Fly with me : algorithms and methods for influencing a flock.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/61905.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-3115-1189. “Fly with me : algorithms and methods for influencing a flock.” 2017. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3115-1189. Fly with me : algorithms and methods for influencing a flock. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/61905.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-3115-1189. Fly with me : algorithms and methods for influencing a flock. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61905

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

7. -7041-9136. Evolutionary neural architecture search for deep learning.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Deep neural networks (DNNs) have produced state-of-the-art results in many benchmarks and problem domains. However, the success of DNNs depends on the proper configuration of… (more)

Subjects/Keywords: Neural architecture search; Deep learning; Neuroevolution; Evolutionary computation; Artificial intelligence

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APA (6th Edition):

-7041-9136. (2019). Evolutionary neural architecture search for deep learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/1388

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7041-9136. “Evolutionary neural architecture search for deep learning.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://dx.doi.org/10.26153/tsw/1388.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7041-9136. “Evolutionary neural architecture search for deep learning.” 2019. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7041-9136. Evolutionary neural architecture search for deep learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Aug 07]. Available from: http://dx.doi.org/10.26153/tsw/1388.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7041-9136. Evolutionary neural architecture search for deep learning. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/1388

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

8. -1871-2757. Discovering multi-purpose modules through deep multitask learning.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Machine learning scientists aim to discover techniques that can be applied across diverse sets of problems. Such techniques need to exploit regularities that are shared… (more)

Subjects/Keywords: Modularity; Multitask learning; Neural networks; Deep learning; Evolutionary computation; Artificial intelligence

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APA (6th Edition):

-1871-2757. (2019). Discovering multi-purpose modules through deep multitask learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/1073

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-1871-2757. “Discovering multi-purpose modules through deep multitask learning.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://dx.doi.org/10.26153/tsw/1073.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-1871-2757. “Discovering multi-purpose modules through deep multitask learning.” 2019. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-1871-2757. Discovering multi-purpose modules through deep multitask learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Aug 07]. Available from: http://dx.doi.org/10.26153/tsw/1073.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-1871-2757. Discovering multi-purpose modules through deep multitask learning. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/1073

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

9. Mahjourian, Reza. Hierarchical policy design for sample-efficient learning of robot table tennis through self-play.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Training robots with physical bodies requires developing new methods and action representations that allow the learning agents to explore the space of policies efficiently. This… (more)

Subjects/Keywords: Robotics; Table tennis; Self-play; Reinforcement learning; Hierarchical policy

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APA (6th Edition):

Mahjourian, R. (2019). Hierarchical policy design for sample-efficient learning of robot table tennis through self-play. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/72812

Chicago Manual of Style (16th Edition):

Mahjourian, Reza. “Hierarchical policy design for sample-efficient learning of robot table tennis through self-play.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/72812.

MLA Handbook (7th Edition):

Mahjourian, Reza. “Hierarchical policy design for sample-efficient learning of robot table tennis through self-play.” 2019. Web. 07 Aug 2020.

Vancouver:

Mahjourian R. Hierarchical policy design for sample-efficient learning of robot table tennis through self-play. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/72812.

Council of Science Editors:

Mahjourian R. Hierarchical policy design for sample-efficient learning of robot table tennis through self-play. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://hdl.handle.net/2152/72812

10. -1564-228X. Modeling and formal verification of gaming storylines.

Degree: PhD, Electrical and Computer engineering, 2016, University of Texas – Austin

 Video games are becoming more and more interactive with increasingly complex plots. These plots typically involve multiple parallel storylines that may converge and diverge based… (more)

Subjects/Keywords: Formal verification; Gaming storyline; Games; Modeling; Modeling tools

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APA (6th Edition):

-1564-228X. (2016). Modeling and formal verification of gaming storylines. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/41455

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-1564-228X. “Modeling and formal verification of gaming storylines.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/41455.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-1564-228X. “Modeling and formal verification of gaming storylines.” 2016. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-1564-228X. Modeling and formal verification of gaming storylines. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/41455.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-1564-228X. Modeling and formal verification of gaming storylines. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/41455

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

11. Stober, Jeremy Michael. Sensorimotor embedding : a developmental approach to learning geometry.

Degree: PhD, Computer Science, 2015, University of Texas – Austin

 A human infant facing the blooming, buzzing confusion of the senses grows up to be an adult with common-sense knowledge of geometry; this knowledge then… (more)

Subjects/Keywords: Sensorimotor; Ai; Robotics; Development

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APA (6th Edition):

Stober, J. M. (2015). Sensorimotor embedding : a developmental approach to learning geometry. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/30532

Chicago Manual of Style (16th Edition):

Stober, Jeremy Michael. “Sensorimotor embedding : a developmental approach to learning geometry.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/30532.

MLA Handbook (7th Edition):

Stober, Jeremy Michael. “Sensorimotor embedding : a developmental approach to learning geometry.” 2015. Web. 07 Aug 2020.

Vancouver:

Stober JM. Sensorimotor embedding : a developmental approach to learning geometry. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/30532.

Council of Science Editors:

Stober JM. Sensorimotor embedding : a developmental approach to learning geometry. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/30532


University of Texas – Austin

12. -6763-2625. Multilayered skill learning and movement coordination for autonomous robotic agents.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 With advances in technology expanding the capabilities of robots, while at the same time making robots cheaper to manufacture, robots are rapidly becoming more prevalent… (more)

Subjects/Keywords: Overlapping layered learning; Role assignment; Reinforcement learning; Robotics; Robot soccer

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APA (6th Edition):

-6763-2625. (2017). Multilayered skill learning and movement coordination for autonomous robotic agents. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62889

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-6763-2625. “Multilayered skill learning and movement coordination for autonomous robotic agents.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/62889.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-6763-2625. “Multilayered skill learning and movement coordination for autonomous robotic agents.” 2017. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-6763-2625. Multilayered skill learning and movement coordination for autonomous robotic agents. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/62889.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-6763-2625. Multilayered skill learning and movement coordination for autonomous robotic agents. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62889

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

13. Huang, Pei-Chi. Real-time robotic tasks for cyber-physical avatars.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 Although modern robots can perform complex tasks using sophisticated algorithms that are specialized to a particular task and environment, creating robots capable of completing tasks… (more)

Subjects/Keywords: Cyber-physical systems; Robotics; Evolutionary computation; Machine learning; Real-time systems; Deep learning; Computer vision; Control

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APA (6th Edition):

Huang, P. (2017). Real-time robotic tasks for cyber-physical avatars. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62985

Chicago Manual of Style (16th Edition):

Huang, Pei-Chi. “Real-time robotic tasks for cyber-physical avatars.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/62985.

MLA Handbook (7th Edition):

Huang, Pei-Chi. “Real-time robotic tasks for cyber-physical avatars.” 2017. Web. 07 Aug 2020.

Vancouver:

Huang P. Real-time robotic tasks for cyber-physical avatars. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/62985.

Council of Science Editors:

Huang P. Real-time robotic tasks for cyber-physical avatars. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62985

14. -7122-1968. Evolving scout agents for military simulations.

Degree: MSin Computer Sciences, Computer Sciences, 2015, University of Texas – Austin

 Simulations play an increasingly significant role in training and preparing the military, particularly in environments with constrained budgets. Unfortunately, in most cases a small number… (more)

Subjects/Keywords: NEAT; Neural networks; Military simulations; Military terrain analysis; Neuroevolution; Autonomous agents

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APA (6th Edition):

-7122-1968. (2015). Evolving scout agents for military simulations. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31850

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7122-1968. “Evolving scout agents for military simulations.” 2015. Masters Thesis, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/31850.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7122-1968. “Evolving scout agents for military simulations.” 2015. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7122-1968. Evolving scout agents for military simulations. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/31850.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7122-1968. Evolving scout agents for military simulations. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31850

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

15. Lessin, Daniel Gregory. Evolved virtual creatures as content : increasing behavioral and morphological complexity.

Degree: PhD, Computer Science, 2014, University of Texas – Austin

 Throughout history, creature-based content has been a highly valued source of entertainment. With the introduction of evolved virtual creatures (or EVCs) by Karl Sims in… (more)

Subjects/Keywords: Artificial life; Content creation; Evolved virtual creatures

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APA (6th Edition):

Lessin, D. G. (2014). Evolved virtual creatures as content : increasing behavioral and morphological complexity. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/28371

Chicago Manual of Style (16th Edition):

Lessin, Daniel Gregory. “Evolved virtual creatures as content : increasing behavioral and morphological complexity.” 2014. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/28371.

MLA Handbook (7th Edition):

Lessin, Daniel Gregory. “Evolved virtual creatures as content : increasing behavioral and morphological complexity.” 2014. Web. 07 Aug 2020.

Vancouver:

Lessin DG. Evolved virtual creatures as content : increasing behavioral and morphological complexity. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2014. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/28371.

Council of Science Editors:

Lessin DG. Evolved virtual creatures as content : increasing behavioral and morphological complexity. [Doctoral Dissertation]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/28371

16. Roller, Stephen Creig. Identifying lexical relationships and entailments with distributional semantics.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 Many modern efforts in Natural Language Understanding depend on rich and powerful semantic representations of words. Systems for sophisticated logical and textual reasoning often depend… (more)

Subjects/Keywords: Natural language processing; Lexical semantics; Lexical relationships; Hypernymy; Distributional semantics

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

APA (6th Edition):

Roller, S. C. (2017). Identifying lexical relationships and entailments with distributional semantics. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61528

Chicago Manual of Style (16th Edition):

Roller, Stephen Creig. “Identifying lexical relationships and entailments with distributional semantics.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/61528.

MLA Handbook (7th Edition):

Roller, Stephen Creig. “Identifying lexical relationships and entailments with distributional semantics.” 2017. Web. 07 Aug 2020.

Vancouver:

Roller SC. Identifying lexical relationships and entailments with distributional semantics. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/61528.

Council of Science Editors:

Roller SC. Identifying lexical relationships and entailments with distributional semantics. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61528

17. Rawal, Aditya, Ph. D. in computer science. Discovering gated recurrent neural network architectures.

Degree: PhD, Computer science, 2019, University of Texas – Austin

 Reinforcement Learning agent networks with memory are a key component in solving POMDP tasks. Gated recurrent networks such as those composed of Long Short-Term Memory… (more)

Subjects/Keywords: Recurrent neural networks; Neuroevolution; Network architecture search; Meta-learning; Reinforcement learning; Language modeling; Music modeling

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APA (6th Edition):

Rawal, Aditya, P. D. i. c. s. (2019). Discovering gated recurrent neural network architectures. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/72839

Chicago Manual of Style (16th Edition):

Rawal, Aditya, Ph D in computer science. “Discovering gated recurrent neural network architectures.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/72839.

MLA Handbook (7th Edition):

Rawal, Aditya, Ph D in computer science. “Discovering gated recurrent neural network architectures.” 2019. Web. 07 Aug 2020.

Vancouver:

Rawal, Aditya PDics. Discovering gated recurrent neural network architectures. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/72839.

Council of Science Editors:

Rawal, Aditya PDics. Discovering gated recurrent neural network architectures. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://hdl.handle.net/2152/72839


University of Texas – Austin

18. Gomez, Faustino John. Robust non-linear control through neuroevolution.

Degree: PhD, Computer Sciences, 2003, University of Texas – Austin

 Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems,… (more)

Subjects/Keywords: Nonlinear control theory; Evolutionary computation; Neural networks (Computer science)

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APA (6th Edition):

Gomez, F. J. (2003). Robust non-linear control through neuroevolution. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/604

Chicago Manual of Style (16th Edition):

Gomez, Faustino John. “Robust non-linear control through neuroevolution.” 2003. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/604.

MLA Handbook (7th Edition):

Gomez, Faustino John. “Robust non-linear control through neuroevolution.” 2003. Web. 07 Aug 2020.

Vancouver:

Gomez FJ. Robust non-linear control through neuroevolution. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2003. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/604.

Council of Science Editors:

Gomez FJ. Robust non-linear control through neuroevolution. [Doctoral Dissertation]. University of Texas – Austin; 2003. Available from: http://hdl.handle.net/2152/604


University of Texas – Austin

19. Mayberry, Marshall Reeves. Incremental nonmonotonic parsing through semantic self-organization.

Degree: PhD, Computer Sciences, 2003, University of Texas – Austin

 Subsymbolic systems have been successfully used to model several aspects of human language processing. Subsymbolic parsers are appealing because they allow combining syntactic, semantic, and… (more)

Subjects/Keywords: Computational linguistics – Statistical methods; Self-organizing systems; Parsing (Computer grammar)

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APA (6th Edition):

Mayberry, M. R. (2003). Incremental nonmonotonic parsing through semantic self-organization. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/763

Chicago Manual of Style (16th Edition):

Mayberry, Marshall Reeves. “Incremental nonmonotonic parsing through semantic self-organization.” 2003. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/763.

MLA Handbook (7th Edition):

Mayberry, Marshall Reeves. “Incremental nonmonotonic parsing through semantic self-organization.” 2003. Web. 07 Aug 2020.

Vancouver:

Mayberry MR. Incremental nonmonotonic parsing through semantic self-organization. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2003. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/763.

Council of Science Editors:

Mayberry MR. Incremental nonmonotonic parsing through semantic self-organization. [Doctoral Dissertation]. University of Texas – Austin; 2003. Available from: http://hdl.handle.net/2152/763


University of Texas – Austin

20. McQuesten, Paul Herbert. Cultural enhancement of neuroevolution.

Degree: PhD, Computer Sciences, 2002, University of Texas – Austin

 Any transmission of behavior from one generation to the next via non–genetic means is a process of culture. Culture provides major advantages for survival in… (more)

Subjects/Keywords: Evolutionary computation; Evolutionary programming (Computer science); Genetic algorithms; Neural networks (Computer science)

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APA (6th Edition):

McQuesten, P. H. (2002). Cultural enhancement of neuroevolution. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/773

Chicago Manual of Style (16th Edition):

McQuesten, Paul Herbert. “Cultural enhancement of neuroevolution.” 2002. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/773.

MLA Handbook (7th Edition):

McQuesten, Paul Herbert. “Cultural enhancement of neuroevolution.” 2002. Web. 07 Aug 2020.

Vancouver:

McQuesten PH. Cultural enhancement of neuroevolution. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2002. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/773.

Council of Science Editors:

McQuesten PH. Cultural enhancement of neuroevolution. [Doctoral Dissertation]. University of Texas – Austin; 2002. Available from: http://hdl.handle.net/2152/773

21. -5025-2877. Cognition in dynamical systems.

Degree: PhD, Mechanical Engineering, 2017, University of Texas – Austin

 Cognition is the process of knowing. As carried out by a dynamical system, it is the process by which the system absorbs information into its… (more)

Subjects/Keywords: Cognition; Dynamical systems; Complex networks; Artificial neural networks; Emergence; Context

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

APA (6th Edition):

-5025-2877. (2017). Cognition in dynamical systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68150

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-5025-2877. “Cognition in dynamical systems.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed August 07, 2020. http://hdl.handle.net/2152/68150.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-5025-2877. “Cognition in dynamical systems.” 2017. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5025-2877. Cognition in dynamical systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2152/68150.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5025-2877. Cognition in dynamical systems. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/68150

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

.