Reinforcement theory

Results: 290



#Item
181Learning to Coordinate Behaviors Pattie Maes & Rodney A. Brooks Al-Laboratory Massachusetts Institute of Technology 545 Technology Square Cambridge, MA 02139

Learning to Coordinate Behaviors Pattie Maes & Rodney A. Brooks Al-Laboratory Massachusetts Institute of Technology 545 Technology Square Cambridge, MA 02139

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Source URL: people.csail.mit.edu

Language: English - Date: 2004-12-08 14:54:35
182Behavioral Approaches to INJURY CONTROL

Behavioral Approaches to INJURY CONTROL

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Source URL: depts.washington.edu

Language: English - Date: 2004-03-30 10:04:38
183Learning Theories  Wikibooks.org March 18, 2013

Learning Theories Wikibooks.org March 18, 2013

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Source URL: upload.wikimedia.org

Language: English - Date: 2013-10-05 05:03:48
184Policy search by dynamic programming  J. Andrew Bagnell Carnegie Mellon University Pittsburgh, PA[removed]Andrew Y. Ng

Policy search by dynamic programming J. Andrew Bagnell Carnegie Mellon University Pittsburgh, PA[removed]Andrew Y. Ng

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Source URL: www.cs.cmu.edu

Language: English - Date: 2004-03-05 16:57:09
185Adapting Control Policies for Expensive Systems to Changing Environments Matthew Tesch, Jeff Schneider, and Howie Choset Abstract— Many controlled systems must operate over a range of external conditions. In this paper

Adapting Control Policies for Expensive Systems to Changing Environments Matthew Tesch, Jeff Schneider, and Howie Choset Abstract— Many controlled systems must operate over a range of external conditions. In this paper

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Source URL: www.cs.cmu.edu

Language: English - Date: 2011-07-26 13:29:57
186Multi-Agent Quadrotor Testbed Control Design: Integral Sliding Mode vs. Reinforcement Learning

Multi-Agent Quadrotor Testbed Control Design: Integral Sliding Mode vs. Reinforcement Learning

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Source URL: www.eecs.berkeley.edu

Language: English - Date: 2007-01-10 18:14:08
187Journal of Artificial Intelligence Research[removed]704  Submitted 09/11; published[removed]Learning to Win by Reading Manuals in a Monte-Carlo Framework

Journal of Artificial Intelligence Research[removed]704 Submitted 09/11; published[removed]Learning to Win by Reading Manuals in a Monte-Carlo Framework

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Source URL: jair.org

Language: English - Date: 2012-04-30 11:59:27
188Reinforcement Learning for Mapping Instructions to Actions S.R.K. Branavan, Harr Chen, Luke S. Zettlemoyer, Regina Barzilay Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology {b

Reinforcement Learning for Mapping Instructions to Actions S.R.K. Branavan, Harr Chen, Luke S. Zettlemoyer, Regina Barzilay Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology {b

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Source URL: people.csail.mit.edu

Language: English - Date: 2009-05-20 11:08:30
189DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes∗ Jennifer L. Barry, Leslie Pack Kaelbling, Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02

DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes∗ Jennifer L. Barry, Leslie Pack Kaelbling, Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02

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Source URL: people.csail.mit.edu

Language: English - Date: 2012-06-11 20:17:47
190DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes∗ Jennifer L. Barry, Leslie Pack Kaelbling, Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02

DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes∗ Jennifer L. Barry, Leslie Pack Kaelbling, Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02

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Source URL: people.csail.mit.edu

Language: English - Date: 2011-09-29 15:55:17