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020 ▼a 9781085609128
035 ▼a (MiAaPQ)AAI13896157
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 150
1001 ▼a Damer, Steven Bjorn.
24510 ▼a Cooperation in Games.
260 ▼a [S.l.]: ▼b University of Minnesota., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 160 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-02, Section: B.
500 ▼a Advisor: Gini, Maria.
5021 ▼a Thesis (Ph.D.)--University of Minnesota, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a 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
590 ▼a School code: 0130.
650 4 ▼a Artificial intelligence.
650 4 ▼a Psychology.
690 ▼a 0800
690 ▼a 0621
71020 ▼a University of Minnesota. ▼b Computer Science.
7730 ▼t Dissertations Abstracts International ▼g 81-02B.
773 ▼t Dissertation Abstract International
790 ▼a 0130
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15491674 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK