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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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Neuroevolution Based Inverse Reinforcement Learning
by Budhraja, Karan Kumar, M.S.  University of Maryland, Baltimore County. 2016: 85 pages; 10140581.
7.
Belief based reinforcement learning for data fusion
by Lollett, Carlos, Ph.D.  State University of New York at Buffalo. 2009: 184 pages; 3342148.
8.
Reinforcement Learning in Structured and Partially Observable Environments
by Azizzadenesheli, Kamyar, Ph.D.  University of California, Irvine. 2019: 170 pages; 13896671.
9.
The neural basis of human reinforcement learning
by Rutledge, Robb B., Ph.D.  New York University. 2010: 259 pages; 3428046.
10.
Tactic-Based Learning for collective learning systems
by Armstrong, Alice, D.Sc.  The George Washington University. 2008: 320 pages; 3304083.
11.
A reinforcement learning model of gaze following
by Jasso, Hector, Ph.D.  University of California, San Diego. 2007: 130 pages; 3259369.
12.
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.
13.
Novel Function Approximation Techniques for Large-scale Reinforcement Learning
by Wu, Cheng, Ph.D.  Northeastern University. 2010: 130 pages; 3443846.
14.
Future Traffic Management System Empowered by Reinforcement Learning and V2X Technologies
by Zhang, Rusheng, Ph.D.  Carnegie Mellon University. 2019: 157 pages; 27545076.
15.
Morphogenetic computing and reinforcement learning for multi-agent systems
by Guo, Hongliang, Ph.D.  Stevens Institute of Technology. 2011: 161 pages; 3557278.
16.
Using Reinforcement Learning in A Simulated Intelligent Tutoring System
by Jasti, Manohar Sai, M.S.  Northern Illinois University. 2019: 54 pages; 13904565.
18.
Learning to Learn with Gradients
by Finn, Chelsea B., Ph.D.  University of California, Berkeley. 2018: 199 pages; 10930398.
19.
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.
20.
Autonomous qualitative learning of distinctions and actions in a developing agent
by Mugan, Jonathan William, Ph.D.  The University of Texas at Austin. 2010: 189 pages; 3428996.
21.
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.
22.
Adaptive control and learning using multiple models
by Wang, Yu, Ph.D.  Yale University. 2017: 229 pages; 10783473.
23.
Deep Networks for Forward Prediction and Planning
by Henaff, Mikael, Ph.D.  New York University. 2018: 164 pages; 10928805.
24.
Interactive Learning for Sequential Decisions and Predictions
by Ross, Stephane, Ph.D.  Carnegie Mellon University. 2013: 294 pages; 3575525.
26.
On the relationship between peers and propensity: Examining vulnerability to peer reinforcement
by Thomas, Kyle J., M.A.  University of Maryland, College Park. 2011: 61 pages; 1506546.
27.
Multi-tier Internet service management: Statistical learning approaches
by Muppala, Sireesha, Ph.D.  University of Colorado at Colorado Springs. 2013: 167 pages; 3560749.
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