000			03364nam a22004335i 4500
001			u374075
003			SIRSI
005			20160812084216.0
007			cr nn 008mamaa
008			100313s2010 gw | s |||| 0|eng d
020			_a9783642116780 _9978-3-642-11678-0
040			_cMX-MeUAM
050		4	_aQ342
082	0	4	_a006.3 _223
100	1		_aMandziuk, Jacek. _eauthor.
245	1	0	_aKnowledge-Free and Learning-Based Methods in Intelligent Game Playing _h[recurso electrónico] / _cby Jacek Mandziuk.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_aXVIII, 254 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStudies in Computational Intelligence, _x1860-949X ; _v276
505	0		_aI: AI Tools and State-of-the-Art Accomplishments in Mind Games -- Foundations of AI and CI in Games. Claude Shannon’s Postulates -- Basic AI Methods and Tools -- State of the Art -- II: CI Methods in Mind Games. Towards Human-Like Playing -- An Overview of Computational Intelligence Methods -- CI in Games – Selected Approaches -- III: An Overview of Challenges and Open Problems -- Evaluation Function Learning -- Game Representation -- Efficient TD Training -- Move Ranking and Search-Free Playing -- Modeling the Opponent and Handling the Uncertainty -- IV: Grand Challenges -- Intuition -- Creativity and Knowledge Discovery -- Multi-game Playing -- Summary and Perspectives.
520			_aThe book is focused on the developments and prospective challenging problems in the area of mind game playing (i.e. playing games that require mental skills) using Computational Intelligence (CI) methods, mainly neural networks, genetic/evolutionary programming and reinforcement learning. The majority of discussed game playing ideas were selected based on their functional similarity to human game playing. These similarities include: learning from scratch, autonomous experience-based improvement and example-based learning. The above features determine the major distinction between CI and traditional AI methods relying mostly on using effective game tree search algorithms, carefully tuned hand-crafted evaluation functions or hardware-based brute-force methods. On the other hand, it should be noted that the aim of this book is by no means to underestimate the achievements of traditional AI methods in game playing domain. On the contrary, the accomplishments of AI approaches are undisputable and speak for themselves. The goal is rather to express my belief that other alternative ways of developing mind game playing machines are possible and urgently needed.
650		0	_aEngineering.
650		0	_aArtificial intelligence.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642116773
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v276
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-11678-0
596			_a19
942			_cLIBRO_ELEC
999			_c201955 _d201955