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Reinforcement theory
Results: 290

#	Item
191	Hierarchical Solution of Large Markov Decision Processes Jennifer Barry and Leslie Pack Kaelbling and Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02139, USA {jbarry,lp Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2010-05-17 16:00:47 Dynamic programming Markov processes Stochastic control Network theory Markov decision process Reinforcement learning Symbol Algorithm Shortest path problem Statistics Mathematics Applied mathematics
192	Hierarchical Solution of Large Markov Decision Processes Jennifer Barry and Leslie Pack Kaelbling and Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02139, USA {jbarry,lp Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2012-06-11 20:17:02 Dynamic programming Markov processes Stochastic control Network theory Markov decision process Reinforcement learning Symbol Algorithm Shortest path problem Statistics Mathematics Applied mathematics
193	Playing is believing: The role of beliefs in multi-agent learning Yu-Han Chang Artificial Intelligence Laboratory Massachusetts Institute of Technology Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2004-07-01 07:47:51 Mathematics Nash equilibrium Strategy Solution concept Minimax Best response Matching pennies Q-learning Reinforcement learning Game theory Problem solving Decision theory
194	Toward Hierachical Decomposition for Planning in Uncertain Environments Terran Lane and Leslie Pack Kaelbling MIT Artificial Intelligence Laboratory Cambridge, MA, 02139 USA terran,lpk @ai.mit.edu Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2004-07-01 07:47:51 Computing Markov processes Markov models Equations Mathematical optimization Markov decision process Reinforcement learning Automated planning and scheduling Bellman equation Statistics Dynamic programming Control theory
195	Hedged learning: Regret-minimization with learning experts Yu-Han Chang [removed] CSAIL, Massachusetts Institute of Technology, 32 Vassar Street, Cambridge, MA[removed]USA Leslie Pack Kaelbling Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2005-11-02 21:38:45 Game theory Cybernetics Machine learning Search algorithms Learning Reinforcement learning Markov decision process Multi-armed bandit Algorithm Statistics Mathematics Applied mathematics
196	Feedback Controller Parameterizations for Reinforcement Learning John W. Roberts Ian R. Manchester Add to Reading List Source URL: groups.csail.mit.edu Language: English - Date: 2011-02-22 01:10:59 Systems science Youla–Kucera parametrization Adaptive control Optimal control Nonlinear control Model predictive control Kalman filter Robust control Automatic control Control theory Systems theory Cybernetics
197	Scaling Up Decentralized MDPs Through Heuristic Search Jilles S. Dibangoye Christopher Amato INRIA Computer Science and AI Laboratory Add to Reading List Source URL: lis.csail.mit.edu Language: English - Date: 2013-03-11 16:08:28 Systems theory Markov processes Stochastic control Equations Mathematical optimization Markov decision process Reinforcement learning Automated planning and scheduling Bellman equation Statistics Dynamic programming Control theory
198	Producing Efficient Error-bounded Solutions for Transition Independent Decentralized MDPs Jilles S. Dibangoye Christopher Amato Add to Reading List Source URL: lis.csail.mit.edu Language: English - Date: 2013-03-11 16:10:29 Dynamic programming Stochastic control Mathematical sciences Markov processes Partially observable Markov decision process Markov decision process Reinforcement learning Algorithm Mathematical optimization Statistics Control theory Operations research
199	Transfer Learning by Discovering Latent Task Parametrizations George Konidaris MIT CSAIL Cambridge, MA[removed]removed] Add to Reading List Source URL: lis.csail.mit.edu Language: English - Date: 2012-11-30 15:08:20 Reinforcement learning Parametrization Statistics Estimation theory Statistical theory Coordinate systems Dimensional analysis Measurement
200	Value Function Approximation in Reinforcement Learning using the Fourier Basis George Konidaris1,3 1 MIT CSAIL [removed] Add to Reading List Source URL: lis.csail.mit.edu Language: English - Date: 2012-06-08 19:46:17 Fourier analysis Numerical analysis Linear algebra Joseph Fourier Spectral theory Fourier series Proto-value functions Gibbs phenomenon Basis function Mathematical analysis Mathematics Algebra