Reinforcement Learning: An Introduction
IReinforcement Learning: An IntroductionSecond edition, in progressRichard S. Sutton and Andrew G. Bartoc 2014, 2015A Bradford BookThe MIT PressCambridge, MassachusettsLondon, EnglandiiIn memory of A. Harry KlopfContentsPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .viiiSeries Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xiiSummary of Notation . . . . . . . . . . . . . . . . . . . . . . . . . .xiii1 The Reinforcement learning Reinforcement learning . . . . . . . . . . . . . . . . . . . . . Examples.
forcement learning in biology and applications. This book was designed to be used as a text in a one- or two-semester course, perhaps supplemented by readings from the literature or by a more mathematical text such as Bertsekas and Tsitsiklis (1996) or Szepesvari (2010). ... xii + >> i> The Reinforcement Learning
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