000 03372nam a22004455i 4500
001 978-3-642-11678-0
003 DE-He213
005 20140220084531.0
007 cr nn 008mamaa
008 100313s2010 gw | s |||| 0|eng d
020 _a9783642116780
_9978-3-642-11678-0
024 7 _a10.1007/978-3-642-11678-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aMańdziuk, Jacek.
_eauthor.
245 1 0 _aKnowledge-Free and Learning-Based Methods in Intelligent Game Playing
_h[electronic resource] /
_cby Jacek Mańdziuk.
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 _uhttp://dx.doi.org/10.1007/978-3-642-11678-0
912 _aZDB-2-ENG
999 _c111906
_d111906