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1.
Learning Neural Representations that Support Efficient Reinforcement Learning
by Stachenfeld, Kimberly, Ph.D.  Princeton University. 2018: 155 pages; 10824319.
2.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
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Analysis of Irregular Event Sequences in Healthcare Using Deep Learning, Reinforcement Learning, and Visualization
by Dabek, Filip, Ph.D.  University of Maryland, Baltimore County. 2020: 268 pages; 28256716.
7.
Reinforcement Learning and Optimal Control in Complex Social Systems
by Yang, Fan, Ph.D.  State University of New York at Buffalo. 2020: 108 pages; 28087042.
8.
Belief based reinforcement learning for data fusion
by Lollett, Carlos, Ph.D.  State University of New York at Buffalo. 2009: 184 pages; 3342148.
9.
Neuroevolution Based Inverse Reinforcement Learning
by Budhraja, Karan Kumar, M.S.  University of Maryland, Baltimore County. 2016: 85 pages; 10140581.
10.
Computational Mechanisms of Selective Attention During Reinforcement Learning
by Radulescu, Angela , Ph.D.  Princeton University. 2020: 133 pages; 27964412.
11.
Optimal reservoir operations for riverine water quality improvement: A reinforcement learning strategy
by Rieker, Jeffrey Donald, Ph.D.  Colorado State University. 2011: 251 pages; 3454631.
12.
Tactic-Based Learning for collective learning systems
by Armstrong, Alice, D.Sc.  The George Washington University. 2008: 320 pages; 3304083.
13.
Novel Function Approximation Techniques for Large-scale Reinforcement Learning
by Wu, Cheng, Ph.D.  Northeastern University. 2010: 130 pages; 3443846.
14.
Reinforcement Learning in Structured and Partially Observable Environments
by Azizzadenesheli, Kamyar, Ph.D.  University of California, Irvine. 2019: 170 pages; 13896671.
15.
The neural basis of human reinforcement learning
by Rutledge, Robb B., Ph.D.  New York University. 2010: 259 pages; 3428046.
16.
A Reinforcement Learning Approach to Sequential Acceptance Sampling as a Critical Success Factor for Lean Six Sigma
by Khalil, Hani Abdulwahab, Ph.D.  The University of Wisconsin - Milwaukee. 2020: 158 pages; 27736208.
17.
A reinforcement learning model of gaze following
by Jasso, Hector, Ph.D.  University of California, San Diego. 2007: 130 pages; 3259369.
18.
Morphogenetic computing and reinforcement learning for multi-agent systems
by Guo, Hongliang, Ph.D.  Stevens Institute of Technology. 2011: 161 pages; 3557278.
19.
Future Traffic Management System Empowered by Reinforcement Learning and V2X Technologies
by Zhang, Rusheng, Ph.D.  Carnegie Mellon University. 2019: 157 pages; 27545076.
20.
Using Reinforcement Learning in A Simulated Intelligent Tutoring System
by Jasti, Manohar Sai, M.S.  Northern Illinois University. 2019: 54 pages; 13904565.
21.
Application of Deep Reinforcement Learning for Intelligent Autonomous Navigation of Car-Like Mobile Robot
by Sivashangaran, Shathushan, M.S.  State University of New York at Buffalo. 2021: 49 pages; 28264977.
23.
Learning to Learn with Gradients
by Finn, Chelsea B., Ph.D.  University of California, Berkeley. 2018: 199 pages; 10930398.
25.
An Investigation of Same/Different Concept Learning in Bumblebees (Bombus impatiens)
by Sayde, Justin M., M.S.  Villanova University. 2011: 45 pages; 1496549.
27.
Inverse optimal control for deterministic continuous-time nonlinear systems
by Johnson, Miles J., Ph.D.  University of Illinois at Urbana-Champaign. 2013: 147 pages; 3632073.
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Exploring the relationship between music learning and mathematics learning in an interdisciplinary Pre-K curriculum
by McDonel, Jennifer S., Ph.D.  State University of New York at Buffalo. 2013: 253 pages; 3598710.
30.
Leveraging Structure for Learning Robot Control and Reactive Planning
by Sutanto, Giovanni, Ph.D.  University of Southern California. 2020: 151 pages; 28086666.
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