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▼a 2018023826
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▼a 9780262039246 (hbk.):
▼c US$80
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▼a 0262039249 (hbk.)
040
▼a  248023
▼c  248023
▼d  248023
100
▼a Sutton, Richard S.
245
▼a  Reinforcement learning:
▼b  an introduction/
▼d  Richard S. Sutton,
▼e  Andrew G. Barto.
250
▼a 2nd ed.
260
▼a  Cambridge, Massachusetts:
▼b  The MIT Press,
▼c  c2018.
300
▼a  xxii, 526 p.:
▼b  ill. (some col.);
▼c  24 cm.
490
▼a Adaptive computation and machine learning series
504
▼a Includes bibliographical references (p. 481-518) and index.
520
▼a "Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms."--
▼c Provided by publisher.
650
▼a Reinforcement learning.
700
▼a Barto, Andrew G.
830
▼a Adaptive computation and machine learning series.
990
▼a 강리원
▼b 강리원
991
▼a 단행본
090
▼a 006.31
▼b S967r2

자료유형 :	단행본
ISBN :	9780262039246 (hbk.):
ISBN :	0262039249 (hbk.)
개인저자 :	Sutton, Richard S.
서명/저자사항 :	Reinforcement learning: an introduction/ Richard S. Sutton, Andrew G. Barto.
판사항 :	2nd ed.
발행사항 :	Cambridge, Massachusetts: The MIT Press, c2018.
형태사항 :	xxii, 526 p.: ill. (some col.); 24 cm.
총서사항 :	Adaptive computation and machine learning series
서지주기 :	Includes bibliographical references (p. 481-518) and index.
요약 :	"Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms."-- Provided by publisher.
일반주제명 :	Reinforcement learning. --
개인저자 :	Barto, Andrew G.
분류기호 :	006.31
언어	영어

해군사관학교 학술정보원