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Volumn 10, Issue 3, 2007, Pages

Evolutionary tournament-based comparison of learning and non-learning algorithms for iterated games

Author keywords

Evolution; Repeated games; Simulation

Indexed keywords


EID: 34547255414     PISSN: 14607425     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (8)

References (25)
  • 2
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    • The Evolution of Strategies in the Iterated Prisoner's Dilemma
    • Lawrence Davis ed, London: Pitman, and Los Altos, CA: Morgan Kaufman
    • AXELROD R (1987) The Evolution of Strategies in the Iterated Prisoner's Dilemma. In Genetic Algorithms and Simulated Annealing, Lawrence Davis (ed.) (London: Pitman, and Los Altos, CA: Morgan Kaufman, 1987), pp. 32-41.
    • (1987) Genetic Algorithms and Simulated Annealing , pp. 32-41
    • AXELROD, R.1
  • 3
    • 34547378263 scopus 로고    scopus 로고
    • Reprinted as Evolving New Strategies, pp. 10-39. in Axelrod, R. M. (1997).
    • Reprinted as Evolving New Strategies, pp. 10-39. in Axelrod, R. M. (1997).
  • 5
    • 34249676853 scopus 로고    scopus 로고
    • Reaching pareto-optimality in prisoner's dilemma using conditional Joint action learning
    • August, Springer Netherlands
    • BANERJEE D and Sen S (2007) Reaching pareto-optimality in prisoner's dilemma using conditional Joint action learning. In Autonomous Agents and Multi-Agent Systems, Volume 15, number 1, August 2007, 91-108, Springer Netherlands
    • (2007) Autonomous Agents and Multi-Agent Systems , vol.15 , Issue.1 , pp. 91-108
    • BANERJEE, D.1    Sen, S.2
  • 8
    • 0036531878 scopus 로고    scopus 로고
    • Multiagent learning using a variable learning rate
    • BOWLING M and Veloso M (2002) Multiagent learning using a variable learning rate. Artificial Intelligence, 136:215-250.
    • (2002) Artificial Intelligence , vol.136 , pp. 215-250
    • BOWLING, M.1    Veloso, M.2
  • 9
    • 0004251138 scopus 로고
    • Cambridge University Press, Cambridge: UK
    • BRAMS S J (1994) Theory of Moves. Cambridge University Press, Cambridge: UK.
    • (1994) Theory of Moves
    • BRAMS, S.J.1
  • 13
    • 0002819121 scopus 로고
    • A comparative analysis of selection schemes used in genetic algorithms
    • Rawlins, G. J, ed, San Mateo, CA: Morgan Kaufman
    • DEB K and Goldberg D (1991) A comparative analysis of selection schemes used in genetic algorithms. In Rawlins, G. J., ed., Foundations of Genetic Algorithms, 69-93. San Mateo, CA: Morgan Kaufman.
    • (1991) Foundations of Genetic Algorithms , pp. 69-93
    • DEB, K.1    Goldberg, D.2
  • 17
    • 0000929496 scopus 로고    scopus 로고
    • Multiagent reinforcement learning: Theoretical framework and an algorithm
    • Shavlik, J, ed, San Francisco, CA: Morgan Kaufmann
    • HU J and Wellman M P (1998) Multiagent reinforcement learning: Theoretical framework and an algorithm. In Shavlik, J., ed., Proceedings of the Fifteenth International Conference on Machine Learning, 242-250. San Francisco, CA: Morgan Kaufmann.
    • (1998) Proceedings of the Fifteenth International Conference on Machine Learning , pp. 242-250
    • HU, J.1    Wellman, M.P.2
  • 18
    • 34547370764 scopus 로고    scopus 로고
    • JAFARI A, Greenwald A, Gondek D and Ercal G (2001) On no-regret learning, fictitious play and Nash equilibrium. In Proceedings of the Eighteenth International Conference on Machine Learning, 226-233, San Francisco, CA: Morgan Kaufmann.
    • JAFARI A, Greenwald A, Gondek D and Ercal G (2001) On no-regret learning, fictitious play and Nash equilibrium. In Proceedings of the Eighteenth International Conference on Machine Learning, 226-233, San Francisco, CA: Morgan Kaufmann.
  • 23
    • 34547377517 scopus 로고    scopus 로고
    • MCKELVEY R D, McLennan A M, and Turocy T L (2005) Gambit: Software Tools for Game Theory, Version 0.2005.06.13
    • MCKELVEY R D, McLennan A M, and Turocy T L (2005) Gambit: Software Tools for Game Theory, Version 0.2005.06.13. http://econweb.tamu.edu/gambit
  • 25
    • 0000940249 scopus 로고
    • Multiagent Reinforcement Learning in the Iterated Prisoner's Dilemma
    • SANDHOLM T and Crites R (1995) Multiagent Reinforcement Learning in the Iterated Prisoner's Dilemma. In Biosystems 37(1:2).
    • (1995) Biosystems , vol.37 , Issue.1 , pp. 2
    • SANDHOLM, T.1    Crites, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.