Interaction of intelligent agents in prisoner's dilemma = 죄수의 딜레마 게임에서 지능형 에이전트의 상호작용

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A model of an intelligent agent based on recurrent neural network is presented and assessed in prisoner``s dilemma game. This method is superior than classical reinforcement learning especially for the ability of searching continuous action and continuous state space. Through experiments, we show that the agent has good adaptation ability to fixed strategies. In the both learning case, it is not guaranteed that they find optimal solution. To overcome this problem, we introduce personality to each agent. This is an attempt to build an agent retaining high adaptation capability to various environment by imitating the inherent property in human. Through evolutionary simulation, we show that the community of agents with personality evolves to bring social prosperity. In addition, the extension to a model of a stockmarket is presented in which independent adaptive agents can buy and sell stock on a central market.
Advisors
Lee, Soo-Youngresearcher이수영researcher
Description
한국과학기술원 : 바이오시스템학과,
Publisher
한국과학기술원
Issue Date
2007
Identifier
264228/325007  / 020053574
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 바이오시스템학과, 2007.2, [ vii, 53 p. ]

Keywords

multiagent systems; prisoner`s dilemma; intelligent agent; recurrent neural network; 회귀 신경 회로망; 멀티에이전트 시스템; 죄수의 딜레마; 지능형 에이전트

URI
http://hdl.handle.net/10203/27139
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=264228&flag=dissertation
Appears in Collection
BiS-Theses_Master(석사논문)
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