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Reinforcement theory
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#	Item
241	Point-based value iteration: An anytime algorithm for POMDPs Joelle Pineau, Geoff Gordon and Sebastian Thrun Carnegie Mellon University Robotics Institute 5000 Forbes Avenue Pittsburgh, PA 15213 Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2003-06-04 12:29:32 Stochastic control Control theory Partially observable Markov decision process Markov decision process Automated planning and scheduling Reinforcement learning Monte Carlo POMDP Statistics Dynamic programming Markov processes
242	Agendas for Multi-Agent Learning Geoffrey J. Gordon December 2006 CMU-ML[removed]School of Computer Science Carnegie Mellon University Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2006-12-20 14:23:06 Artificial intelligence Outcome Pareto efficiency Nash equilibrium Mathematical optimization Agent-based model Welfare economics Reinforcement learning Subgame Game theory Problem solving Science
243	Multiagent Learning in the Presence of Agents with Limitations Michael Bowling May 14, 2003 CMU-CS[removed] Add to Reading List Source URL: reports-archive.adm.cs.cmu.edu Language: English - Date: 2003-07-21 09:06:25 Knowledge Academia Artificial intelligence Year of birth missing Multi-agent systems Reinforcement learning Agent-based model Nash equilibrium Carnegie Mellon School of Computer Science Science Game theory Formal sciences
244	Approximate Solutions For Partially Observable Stochastic Games with Common Payoffs Rosemary Emery-Montemerlo, Geoff Gordon, Jeff Schneider School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2004-06-25 15:30:50 Stochastic control Bayesian statistics Artificial intelligence Partially observable Markov decision process Bayesian game Action selection Reinforcement learning Markov decision process Decision theory Statistics Dynamic programming Markov processes
245	Policy-contingent abstraction for robust robot control Joelle Pineau, Geoff Gordon and Sebastian Thrun School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2003-06-04 12:29:33 Stochastic control Control theory Partially observable Markov decision process Reinforcement learning Markov decision process Automated planning and scheduling Action selection Bellman equation Abstraction Statistics Dynamic programming Markov processes
246	No-Regret Learning and a Mechanism for Distributed Multiagent Planning Jan-P. Calliess Geoffrey J. Gordon Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2008-02-18 10:33:25 Loss function Reinforcement learning Forcing Price of anarchy Game theory Statistics Mechanism design
247	ICML 2012 Handbook International Conference on Machine Learning June 26 - July 1, 2012 Edinburgh, Scotland, UK Add to Reading List Source URL: icml.cc Language: English - Date: 2012-06-14 13:31:31 International Conference on Machine Learning Reinforcement learning Informatics Forum Computational learning theory Scottish Informatics and Computer Science Alliance Artificial intelligence Machine learning Learning
248	Selecting Computations: Theory and Applications Nicholas Hay and Stuart Russell Computer Science Division University of California Berkeley, CA 94720 Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2012-10-04 09:08:48 Decision theory Markov models Mathematical optimization Dynamic programming Reinforcement learning Markov decision process Markov chain Value of information Variance Statistics Probability and statistics Markov processes
249	State Abstraction for Programmable Reinforcement Learning Agents David Andre and Stuart J. Russell Computer Science Division, UC Berkeley, CA[removed]fdandre,[removed] Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2008-01-03 13:48:15 Mathematical optimization Dynamic programming Equations Operations research Systems engineering Reinforcement learning Q-learning Markov decision process Bellman equation Statistics Systems theory Control theory
250	Q-Decomposition for Reinforcement Learning Agents Stuart Russell @.. Andrew L. Zimdars @.. Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2003-06-03 00:44:40 Systems theory Equations Mathematical optimization SARSA Q-learning Markov processes Stochastic control Reinforcement learning Markov decision process Statistics Control theory Dynamic programming

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