TAP: An effective personality representation for inter-Agent adaptation in games

Tan, CT; Cheng, HL

TAP: An effective personality representation for inter-Agent adaptation in games

Tan, CT Cheng, HL

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 4th Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE 2008, 2008, pp. 120 - 125
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Tan, CT	en_US
dc.contributor.author	Cheng, HL	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	Proceedings of the 4th Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE 2008, 2008, pp. 120 - 125	en_US
dc.identifier.isbn	9781577353911	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16289
dc.description.abstract	Tactical Agent Personality (TAP) is a modeling concept to capture tactical patterns in game agents, based on a personality concept introduced by Tan and Cheng (2007), to allow behavior adaptation to different play styles. We introduced a weighted sequential topology to the actions set to capture tactical preferences rather than individual action preferences. This produces a personality representation of much higher expressive power that improves the adaptation performance and subsequently enables a larger variety of action genres to be adaptable. A TAP-based learning framework is then constructed and it is shown to perform better than the one based on the previous agent personality. Consequently, we also implement an RPG scenario that demonstrates its ability to generate adaptive plausible behavior in a much larger variety of action genres. Copyright © 2008, Association for the Advancement of Artificial Intelligence.	en_US
dc.relation.ispartof	Proceedings of the 4th Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE 2008	en_US
dc.title	TAP: An effective personality representation for inter-Agent adaptation in games	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Stanford, USA	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - HCTD - Human Centred Technology Design
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Tactical Agent Personality (TAP) is a modeling concept to capture tactical patterns in game agents, based on a personality concept introduced by Tan and Cheng (2007), to allow behavior adaptation to different play styles. We introduced a weighted sequential topology to the actions set to capture tactical preferences rather than individual action preferences. This produces a personality representation of much higher expressive power that improves the adaptation performance and subsequently enables a larger variety of action genres to be adaptable. A TAP-based learning framework is then constructed and it is shown to perform better than the one based on the previous agent personality. Consequently, we also implement an RPG scenario that demonstrates its ability to generate adaptive plausible behavior in a much larger variety of action genres. Copyright © 2008, Association for the Advancement of Artificial Intelligence.

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http://hdl.handle.net/10453/16289