000			01714nam a2200325 i 4500
999			_c40312 _d40312
001			346888
003			BD-DhAAL
005			20211110120446.0
008			190519t2018 maua b 001 0 eng
010			_a 2018023826
020			_a9780262039246 (hardcover : alk. paper)
040			_aDLC _beng _cDLC _erda _dDLC _dBD-DhAAL
042			_apcc
050	0	0	_aQ325.6 _b.R45 2018
082	0	0	_a006.31 _223
100	1		_aSutton, Richard S., _eauthor. _931666
245	1	0	_aReinforcement learning : _ban introduction / _cRichard S. Sutton and Andrew G. Barto.
250			_aSecond edition.
260			_aCambridge, Massachusetts : _bThe MIT Press, _cc2018
300			_axxii, 526 pages : _billustrations (some color) ; _c23 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."--
526			_aCSE
650		0	_aReinforcement learning. _931667
650		0	_aComputer science. _942479
700	1		_aBarto, Andrew G., _eauthor. _931668
852			_aAyesha Abed Library _cGeneral Stacks
942			_2ddc _cBK