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Volumn , Issue , 2012, Pages 587-604

Safe opponent exploitation

Author keywords

game theory; multiagent learning; opponent exploitation

Indexed keywords

BEST RESPONSE; EQUILIBRIUM STRATEGY; GAME-THEORETIC; MULTI-AGENT LEARNING; OPPONENT EXPLOITATION; TEST PROBLEM; TIME STEP; ZERO-SUM GAME;

EID: 84863535666     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2229012.2229056     Document Type: Conference Paper
Times cited : (9)

References (17)
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    • Bowling, M.1    Johanson, M.2    Burch, N.3    Szafron, D.4
  • 3
    • 84859421504 scopus 로고    scopus 로고
    • Computing equilibria by incorporating qualitative models
    • GANZFRIED, S. AND SANDHOLM, T. 2010. Computing equilibria by incorporating qualitative models. AAMAS.
    • (2010) AAMAS
    • Ganzfried, S.1    Sandholm, T.2
  • 4
    • 84899449920 scopus 로고    scopus 로고
    • Game theory-based opponent modeling in large imperfect-information games
    • GANZFRIED, S. AND SANDHOLM, T. 2011. Game theory-based opponent modeling in large imperfect-information games. AAMAS.
    • (2011) AAMAS
    • Ganzfried, S.1    Sandholm, T.2
  • 6
    • 84876942189 scopus 로고    scopus 로고
    • Automated action abstraction of imperfect information extensive-form games
    • HAWKIN, J., HOLTE, R., AND SZAFRON, D. 2011. Automated action abstraction of imperfect information extensive-form games. AAAI.
    • (2011) AAAI
    • Hawkin, J.1    Holte, R.2    Szafron, D.3
  • 8
    • 84863526230 scopus 로고    scopus 로고
    • Effective short-term opponent exploitation in simplified poker
    • HOEHN, B., SOUTHEY, F., HOLTE, R. C., AND BULITKO, V. 2005. Effective short-term opponent exploitation in simplified poker. AAAI.
    • (2005) AAAI
    • Hoehn, B.1    Southey, F.2    Holte, R.C.3    Bulitko, V.4
  • 10
    • 0027964134 scopus 로고
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    • KOLLER, D., MEGIDDO, N., AND VON STENGEL, B. 1994. Fast algorithms for finding randomized strategies in game trees. STOC.
    • (1994) STOC
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  • 11
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    • KOLLER, D. AND PFEFFER, A. 1997. Representations and solutions for game-theoretic problems. Artificial Intelligence 94.
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    • Koller, D.1    Pfeffer, A.2
  • 12
  • 14
    • 34147097403 scopus 로고    scopus 로고
    • A general criterion and an algorithmic framework for learning in multi-agent systems
    • POWERS, R., SHOHAM, Y., AND VU, T. 2007. A general criterion and an algorithmic framework for learning in multi-agent systems. Machine Learning 67.
    • (2007) Machine Learning , vol.67
    • Powers, R.1    Shoham, Y.2    Vu, T.3
  • 15
    • 34249045960 scopus 로고    scopus 로고
    • Perspectives on multiagent learning
    • SANDHOLM, T. 2007. Perspectives on multiagent learning. Artificial Intelligence 171.
    • (2007) Artificial Intelligence , vol.171
    • Sandholm, T.1
  • 17


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.