000 03237nam a22004935i 4500
001 978-3-319-33459-2
003 DE-He213
005 20200421111853.0
007 cr nn 008mamaa
008 160922s2016 gw | s |||| 0|eng d
020 _a9783319334592
_9978-3-319-33459-2
024 7 _a10.1007/978-3-319-33459-2
_2doi
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aMerrick, Kathryn E.
_eauthor.
245 1 0 _aComputational Models of Motivation for Game-Playing Agents
_h[electronic resource] /
_cby Kathryn E. Merrick.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXVII, 213 p. 66 illus., 23 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aFrom Player Types to Motivation -- Computational Models of Achievement, Affiliation, and Power Motivation -- Game Playing Agents and Non-player Characters -- Achievement Motivation -- Profiles of Achievement, Affiliation, and Power Motivation -- Enemies -- Pets and Partner Characters -- Support Characters -- Evolution of Motivated Agents -- Conclusion and Future Work. .
520 _aThe focus of this book is on three influential cognitive motives: achievement, affiliation, and power motivation. Incentive-based theories of achievement, affiliation and power motivation are the basis for competence-seeking behaviour, relationship-building, leadership, and resource-controlling behaviour in humans. In this book we show how these motives can be modelled and embedded in artificial agents to achieve behavioural diversity. Theoretical issues are addressed for representing and embedding computational models of motivation in rule-based agents, learning agents, crowds and evolution of motivated agents. Practical issues are addressed for defining games, mini-games or in-game scenarios for virtual worlds in which computer-controlled, motivated agents can participate alongside human players. The book is structured into four parts: game playing in virtual worlds by humans and agents; comparing human and artificial motives; game scenarios for motivated agents; and evolution and the future of motivated game-playing agents. It will provide game programmers, and those with an interest in artificial intelligence, with the knowledge required to develop diverse, believable game-playing agents for virtual worlds.
650 0 _aComputer science.
650 0 _aData mining.
650 0 _aArtificial intelligence.
650 0 _aComputational intelligence.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aComputational Intelligence.
650 2 4 _aData Mining and Knowledge Discovery.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319334578
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-33459-2
912 _aZDB-2-SCS
942 _cEBK
999 _c56256
_d56256