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Cooperation in Games
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Cooperation in Games. |
| 개인저자 | Damer, Steven Bjorn. |
| 단체저자명 | University of Minnesota. Computer Science. |
| 발행사항 | [S.l.]: University of Minnesota., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 160 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-02B. Dissertation Abstract International |
| ISBN | 9781085609128 |
| 학위논문주기 | Thesis (Ph.D.)--University of Minnesota, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-02, Section: B.
Advisor: Gini, Maria. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | This dissertation explores several problems related to social behavior, which is a complex and difficult problem. In this dissertation we describe ways to solve problems for agents interacting with opponents, specifically (1) identifying cooperative strategies,(2) acting on fallible predictions, and (3) determining how much to compromise with the opponent. In a multi-agent environment an agent's interactions with its opponent can significantly affect its performance. However, it is not always possible for the agent to fully model the behavior of the opponent and compute a best response. We present three algorithms for agents to use when interacting with an opponent too complex to be modelled. An agent which wishes to cooperate with its opponent must first identify what strategy constitutes a cooperative action. We address the problem of identifying cooperative strategies in repeated randomly generated games by modelling an agent's intentions with a real number, its attitude, which is used to produce a modified game |
| 일반주제명 | Artificial intelligence. Psychology. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
