Transcription of Algorithms for Reinforcement Learning
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Algorithms for Reinforcement LearningDraft of the lecture published in theSynthesis Lectures on Artificial Intelligence and Machine LearningseriesbyMorgan & Claypool PublishersCsaba Szepesv ariJune 9, 2009 Contents1 Overview32 Markov decision Preliminaries .. Markov Decision Processes .. Value functions .. Dynamic programming Algorithms for solving MDPs ..163 Value prediction Temporal difference Learning in finite state spaces .. TD(0) .. Monte-Carlo .. ( ): Unifying Monte-Carlo and TD(0) .. Algorithms for large state spaces.
focuses on policy gradient methods. Powell (2007) presents the algorithms and ideas from an ... (although an appendix is added that explains these basic results). Apart from these, the book aims to cover a bit of all aspects of RL, up to the level that the reader should be
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