Presentation	2003/1/23 Rationarity and multiagent simulation Kiyoshi IZUMI,
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Abstract(in English)	In this paper, we constructed three types of agents, which are different in efficiency and accuracy of learning. They were compared using acquired payoff in a game-theoretic situation that is called Minority game. As a result, when the complexity of environmental change is low and the learning speed of others' models is high, agents that used simpler learning method with little information got higher payoff, and when the learning speed of others' models is low, agents that used accurate learning method with full information got higher payoff. When the complexity of environmental change is higher, agents that used intermediate learning method got higher payoff.
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Keyword(in English)	Minority game / Complexity / Multiagent systems / Learning
Paper #	AI2002-38
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Conference Information
Committee	AI
Conference Date	2003/1/23(1days)
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Paper Information
Registration To	Artificial Intelligence and Knowledge-Based Processing (AI)
Language	JPN
Title (in Japanese)	(See Japanese page)
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Title (in English)	Rationarity and multiagent simulation
Sub Title (in English)
Keyword(1)	Minority game
Keyword(2)	Complexity
Keyword(3)	Multiagent systems
Keyword(4)	Learning
1st Author's Name	Kiyoshi IZUMI
1st Author's Affiliation	Cyber Assist Research Center,AIST()
Date	2003/1/23
Paper #	AI2002-38
Volume (vol)	vol.102
Number (no)	614
Page	pp.pp.-
#Pages	6
Date of Issue