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You searched for +publisher:"U of Massachusetts : PhD" +contributor:("Andrew G. Barto"). Showing records 1 – 10 of 10 total matches.

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1. Konidaris, George D. Autonomous Robot Skill Acquisition.

Degree: PhD, Computer Science, 2011, U of Massachusetts : PhD

  Among the most impressive of aspects of human intelligence is skill acquisition—the ability to identify important behavioral components, retain them as skills, refine them… (more)

Subjects/Keywords: Reinforcement Learning; Robotics; Skill Acquisition; Artificial Intelligence and Robotics; Computer Sciences

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APA (6th Edition):

Konidaris, G. D. (2011). Autonomous Robot Skill Acquisition. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/384

Chicago Manual of Style (16th Edition):

Konidaris, George D. “Autonomous Robot Skill Acquisition.” 2011. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/384.

MLA Handbook (7th Edition):

Konidaris, George D. “Autonomous Robot Skill Acquisition.” 2011. Web. 17 Nov 2019.

Vancouver:

Konidaris GD. Autonomous Robot Skill Acquisition. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2011. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/384.

Council of Science Editors:

Konidaris GD. Autonomous Robot Skill Acquisition. [Doctoral Dissertation]. U of Massachusetts : PhD; 2011. Available from: https://scholarworks.umass.edu/open_access_dissertations/384

2. Cooper, David G. Computational Affect Detection for Education and Health.

Degree: PhD, Computer Science, 2011, U of Massachusetts : PhD

  Emotional intelligence has a prominent role in education, health care, and day to day interaction. With the increasing use of computer technology, computers are… (more)

Subjects/Keywords: affect detection; intelligent tutoring systems; linear classifiers; multimodal sensors; speech prosody; visual tracking; Computer Sciences

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APA (6th Edition):

Cooper, D. G. (2011). Computational Affect Detection for Education and Health. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/437

Chicago Manual of Style (16th Edition):

Cooper, David G. “Computational Affect Detection for Education and Health.” 2011. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/437.

MLA Handbook (7th Edition):

Cooper, David G. “Computational Affect Detection for Education and Health.” 2011. Web. 17 Nov 2019.

Vancouver:

Cooper DG. Computational Affect Detection for Education and Health. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2011. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/437.

Council of Science Editors:

Cooper DG. Computational Affect Detection for Education and Health. [Doctoral Dissertation]. U of Massachusetts : PhD; 2011. Available from: https://scholarworks.umass.edu/open_access_dissertations/437

3. Wolfe, Alicia Peregrin. Paying Attention to What Matters: Observation Abstraction in Partially Observable Environments.

Degree: PhD, Computer Science, 2010, U of Massachusetts : PhD

 Autonomous agents may not have access to complete information about the state of the environment. For example, a robot soccer player may only be able… (more)

Subjects/Keywords: Observation abstraction; Partially observable environments; Computer Sciences

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APA (6th Edition):

Wolfe, A. P. (2010). Paying Attention to What Matters: Observation Abstraction in Partially Observable Environments. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/188

Chicago Manual of Style (16th Edition):

Wolfe, Alicia Peregrin. “Paying Attention to What Matters: Observation Abstraction in Partially Observable Environments.” 2010. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/188.

MLA Handbook (7th Edition):

Wolfe, Alicia Peregrin. “Paying Attention to What Matters: Observation Abstraction in Partially Observable Environments.” 2010. Web. 17 Nov 2019.

Vancouver:

Wolfe AP. Paying Attention to What Matters: Observation Abstraction in Partially Observable Environments. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2010. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/188.

Council of Science Editors:

Wolfe AP. Paying Attention to What Matters: Observation Abstraction in Partially Observable Environments. [Doctoral Dissertation]. U of Massachusetts : PhD; 2010. Available from: https://scholarworks.umass.edu/open_access_dissertations/188

4. Katz, Dov. Interactive Perception of Articulated Objects for Autonomous Manipulation.

Degree: PhD, Computer Science, 2011, U of Massachusetts : PhD

  This thesis develops robotic skills for manipulating novel articulated objects. The degrees of freedom of an articulated object describe the relationship among its rigid… (more)

Subjects/Keywords: Articulated Objects; Interactive Perception; Manipulation; Reinforcement Learning; Rigid Body; Computer Sciences

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APA (6th Edition):

Katz, D. (2011). Interactive Perception of Articulated Objects for Autonomous Manipulation. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/468

Chicago Manual of Style (16th Edition):

Katz, Dov. “Interactive Perception of Articulated Objects for Autonomous Manipulation.” 2011. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/468.

MLA Handbook (7th Edition):

Katz, Dov. “Interactive Perception of Articulated Objects for Autonomous Manipulation.” 2011. Web. 17 Nov 2019.

Vancouver:

Katz D. Interactive Perception of Articulated Objects for Autonomous Manipulation. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2011. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/468.

Council of Science Editors:

Katz D. Interactive Perception of Articulated Objects for Autonomous Manipulation. [Doctoral Dissertation]. U of Massachusetts : PhD; 2011. Available from: https://scholarworks.umass.edu/open_access_dissertations/468

5. Johns, Jeffrey Thomas. Basis Construction and Utilization for Markov Decision Processes Using Graphs.

Degree: PhD, Computer Science, 2010, U of Massachusetts : PhD

 The ease or difficulty in solving a problemstrongly depends on the way it is represented. For example, consider the task of multiplying the numbers 12… (more)

Subjects/Keywords: Markov decision process; Reinforcement learning; Representation discovery; Computer Sciences

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APA (6th Edition):

Johns, J. T. (2010). Basis Construction and Utilization for Markov Decision Processes Using Graphs. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/177

Chicago Manual of Style (16th Edition):

Johns, Jeffrey Thomas. “Basis Construction and Utilization for Markov Decision Processes Using Graphs.” 2010. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/177.

MLA Handbook (7th Edition):

Johns, Jeffrey Thomas. “Basis Construction and Utilization for Markov Decision Processes Using Graphs.” 2010. Web. 17 Nov 2019.

Vancouver:

Johns JT. Basis Construction and Utilization for Markov Decision Processes Using Graphs. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2010. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/177.

Council of Science Editors:

Johns JT. Basis Construction and Utilization for Markov Decision Processes Using Graphs. [Doctoral Dissertation]. U of Massachusetts : PhD; 2010. Available from: https://scholarworks.umass.edu/open_access_dissertations/177

6. Niekum, Scott D. Semantically Grounded Learning from Unstructured Demonstrations.

Degree: PhD, Computer Science, 2013, U of Massachusetts : PhD

  Robots exhibit flexible behavior largely in proportion to their degree of semantic knowledge about the world. Such knowledge is often meticulously hand-coded for a… (more)

Subjects/Keywords: Bayesian nonparametrics; Learning from demonstration; PR2; Robotics; Computer Sciences; Robotics

…Directed by: Professor Andrew G. Barto Robots exhibit flexible behavior largely in proportion to… 

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APA (6th Edition):

Niekum, S. D. (2013). Semantically Grounded Learning from Unstructured Demonstrations. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/811

Chicago Manual of Style (16th Edition):

Niekum, Scott D. “Semantically Grounded Learning from Unstructured Demonstrations.” 2013. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/811.

MLA Handbook (7th Edition):

Niekum, Scott D. “Semantically Grounded Learning from Unstructured Demonstrations.” 2013. Web. 17 Nov 2019.

Vancouver:

Niekum SD. Semantically Grounded Learning from Unstructured Demonstrations. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2013. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/811.

Council of Science Editors:

Niekum SD. Semantically Grounded Learning from Unstructured Demonstrations. [Doctoral Dissertation]. U of Massachusetts : PhD; 2013. Available from: https://scholarworks.umass.edu/open_access_dissertations/811

7. Levy, Yariv Z. Multiscale Modeling of Human Addiction: a Computational Hypothesis for Allostasis and Healing.

Degree: PhD, Computer Science, 2013, U of Massachusetts : PhD

  This dissertation presents a computational multiscale framework for predicting behavioral tendencies related to human addiction. The research encompasses three main contributions. The first contribution… (more)

Subjects/Keywords: cognitive learning; computational biology; high dimensional dynamical system; knowledge repository model; natural recovery; Computer Sciences

…Directed by: Professor Andrew G. Barto and Professor Jerrold S. Meyer This dissertation presents… 

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APA (6th Edition):

Levy, Y. Z. (2013). Multiscale Modeling of Human Addiction: a Computational Hypothesis for Allostasis and Healing. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/720

Chicago Manual of Style (16th Edition):

Levy, Yariv Z. “Multiscale Modeling of Human Addiction: a Computational Hypothesis for Allostasis and Healing.” 2013. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/720.

MLA Handbook (7th Edition):

Levy, Yariv Z. “Multiscale Modeling of Human Addiction: a Computational Hypothesis for Allostasis and Healing.” 2013. Web. 17 Nov 2019.

Vancouver:

Levy YZ. Multiscale Modeling of Human Addiction: a Computational Hypothesis for Allostasis and Healing. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2013. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/720.

Council of Science Editors:

Levy YZ. Multiscale Modeling of Human Addiction: a Computational Hypothesis for Allostasis and Healing. [Doctoral Dissertation]. U of Massachusetts : PhD; 2013. Available from: https://scholarworks.umass.edu/open_access_dissertations/720

8. Kuindersma, Scott Robert. Variable Risk Policy Search for Dynamic Robot Control.

Degree: PhD, Computer Science, 2012, U of Massachusetts : PhD

  A central goal of the robotics community is to develop general optimization algorithms for producing high-performance dynamic behaviors in robot systems. This goal is… (more)

Subjects/Keywords: Bayesian; control; optimization; policy search; risk-sensitive; robotics; Computer Sciences

…Grupen and Professor Andrew G. Barto A central goal of the robotics community is to develop… 

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APA (6th Edition):

Kuindersma, S. R. (2012). Variable Risk Policy Search for Dynamic Robot Control. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/650

Chicago Manual of Style (16th Edition):

Kuindersma, Scott Robert. “Variable Risk Policy Search for Dynamic Robot Control.” 2012. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/650.

MLA Handbook (7th Edition):

Kuindersma, Scott Robert. “Variable Risk Policy Search for Dynamic Robot Control.” 2012. Web. 17 Nov 2019.

Vancouver:

Kuindersma SR. Variable Risk Policy Search for Dynamic Robot Control. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2012. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/650.

Council of Science Editors:

Kuindersma SR. Variable Risk Policy Search for Dynamic Robot Control. [Doctoral Dissertation]. U of Massachusetts : PhD; 2012. Available from: https://scholarworks.umass.edu/open_access_dissertations/650

9. Manfredi, Victoria U. Sensor Control and Scheduling Strategies for Sensor Networks.

Degree: PhD, Computer Science, 2009, U of Massachusetts : PhD

  We investigate sensor control and scheduling strategies to most effectively use the limited resources of an ad hoc network or closed-loop sensor network. In… (more)

Subjects/Keywords: Resource Constraints; Routing; Scheduling; Sensor Control; Sensor Networks; Computer Sciences

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APA (6th Edition):

Manfredi, V. U. (2009). Sensor Control and Scheduling Strategies for Sensor Networks. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/105

Chicago Manual of Style (16th Edition):

Manfredi, Victoria U. “Sensor Control and Scheduling Strategies for Sensor Networks.” 2009. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/105.

MLA Handbook (7th Edition):

Manfredi, Victoria U. “Sensor Control and Scheduling Strategies for Sensor Networks.” 2009. Web. 17 Nov 2019.

Vancouver:

Manfredi VU. Sensor Control and Scheduling Strategies for Sensor Networks. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2009. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/105.

Council of Science Editors:

Manfredi VU. Sensor Control and Scheduling Strategies for Sensor Networks. [Doctoral Dissertation]. U of Massachusetts : PhD; 2009. Available from: https://scholarworks.umass.edu/open_access_dissertations/105

10. Osentoski, Sarah. Action-Based Representation Discovery in Markov Decision Processes.

Degree: PhD, Computer Science, 2009, U of Massachusetts : PhD

  This dissertation investigates the problem of representation discovery in discrete Markov decision processes, namely how agents can simultaneously learn representation and optimal control. Previous… (more)

Subjects/Keywords: Machine Learning; Reinforcement Learning; Computer Sciences

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APA (6th Edition):

Osentoski, S. (2009). Action-Based Representation Discovery in Markov Decision Processes. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/119

Chicago Manual of Style (16th Edition):

Osentoski, Sarah. “Action-Based Representation Discovery in Markov Decision Processes.” 2009. Doctoral Dissertation, U of Massachusetts : PhD. Accessed November 17, 2019. https://scholarworks.umass.edu/open_access_dissertations/119.

MLA Handbook (7th Edition):

Osentoski, Sarah. “Action-Based Representation Discovery in Markov Decision Processes.” 2009. Web. 17 Nov 2019.

Vancouver:

Osentoski S. Action-Based Representation Discovery in Markov Decision Processes. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2009. [cited 2019 Nov 17]. Available from: https://scholarworks.umass.edu/open_access_dissertations/119.

Council of Science Editors:

Osentoski S. Action-Based Representation Discovery in Markov Decision Processes. [Doctoral Dissertation]. U of Massachusetts : PhD; 2009. Available from: https://scholarworks.umass.edu/open_access_dissertations/119

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