Shivaram's Reading List


Function Approximation     Partial Observability     Learning Methods     Ensembles    
Stochastic Optimisation     General RL     General ML     Multiagent Learning    
Comparison/Integration     Bandits     Applications     Robot Soccer    
Humanoids     Parameter     MDP     Empirical    
Failure Warning     Representation     General AI     Neural Networks    
All    

MDP

Success, strategy and skill: an experimental study
Christopher Archibald, Alon Altman, and Yoav Shoham, 2010
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SZ-Tetris as a Benchmark for Studying Key Problems of Reinforcement Learning
István Szita and Csaba Szepesvári, 2010
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Improvements on Learning Tetris with Cross-Entropy
Christophe Thierry and Bruno Scherrer, 2010
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Building Controllers for Tetris
Christophe Thierry and Bruno Scherrer, 2010
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Modeling billiards games
Christopher Archibald and Yoav Shoham, 2009
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On the Evolution of Artificial Tetris Players
Amine Boumaza, 2009
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Biasing Approximate Dynamic Programming with a Lower Discount Factor
Marek Petrik and Bruno Scherrer, 2009
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Cross-Entropy Method for Reinforcement Learning
Steijn Kistemaker, 2008
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Tetris: A Study of Randomized Constraint Sampling
Vivek F. Farias and Benjamin Van Roy, 2006
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Learning Tetris using the noisy cross-entropy method
István Szita and András L\Horincz, 2006
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An Evolutionary Approach to Tetris
Niko Böhm, Gabriella Kókai, and Stefan Mandl, 2005
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An Adaptive Sampling Algorithm for Solving Markov Decision Processes
Hyeong Soo Chang, Michael C. Fu, Jiaqiao Hu, and Steven I. Marcus, 2005
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Evolving a Neural Network Location Evaluator to Play Ms. Pac-Man
Simon M. Lucas, 2005
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Tetris is hard, even to approximate
Ron Breukelaar, Erik D. Demaine, Susan Hohenberger, Hendrik Jan Hoogeboom, Walter A. Kosters, and David Liben-Nowell, 2004
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On the Numeric Stability of Gaussian Processes Regression for Relational Reinforcement Learning
Jan Ramon and Kurt Driessens, 2004
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Learning to play Pac-Man: An Evolutionary, Rule-based Approach
Marcus Gallagher and Amanda Ryan, 2003
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An Agent that Learns to Play Pacman
Donald Shepherd, 2003
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A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
Michael Kearns, Yishay Mansour, and Andrew Y. Ng, 2002
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Least-Squares Methods in Reinforcement Learning for Control
Michail G. Lagoudakis, Ronald Parr, and Michael L. Littman, 2002
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A Natural Policy Gradient
Sham Kakade, 2001
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How to Lose at Tetris
Heidi Burgiel, 1997
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Neuro-Dynamic Programming
Dimitri P. Bertsekas and John N. Tsitsiklis, 1996
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Evolution-Based Discovery of Hierarchical Behaviors
Justinian P. Rosca and Dana H. Ballard, 1996
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