000			01553cam a2200313 i 4500
001			20515853
003			OSt
005			20211012150848.0
008			180525s2018 maua b 001 0 eng
010			_a 2018023826
020			_a9780262039246 (hardcover : alk. paper)
040			_aDLC _beng _cIISERB _erda _dDLC
042			_apcc
050	0	0	_aQ325.6 _b.R45 2018
082	0	0	_a006.31 So7R2 _223
100	1		_aSutton, Richard S. _eauthor. _927364
245	1	0	_aReinforcement learning : _ban introduction _cRichard S. Sutton and Andrew G. Barto.
250			_aSecond edition.
260			_aCambridge: _bThe MIT Press, _c2020.
300			_axxii, 526 pages : _billustrations (some color) ; _c24 cm.
490	0		_aAdaptive computation and machine learning series
504			_aIncludes bibliographical references (pages 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."--
650		0	_aReinforcement learning. _927365
700	1		_aBarto, Andrew G. _eauthor. _927366
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c9591 _d9591