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Volumn , Issue , 2007, Pages 1041-1046

Transfer learning in real-time strategy games using hybrid CBR/RL

Author keywords

[No Author keywords available]

Indexed keywords

CASEBASED REASONINGS (CBR); CBR; GAME AI; IMPROVE PERFORMANCE; MULTILAYERED ARCHITECTURE; PERFORMANCE GAIN; REAL-TIME STRATEGY GAMES; TRANSFER LEARNING;

EID: 80054035256     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (116)

References (12)
  • 1
    • 0028401306 scopus 로고
    • Case-based reasoning: Foundational issues, methodological variations, and system approaches
    • Agnar Aamodt and Enric Plaza. Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications, 7(1):39-59, 1994.
    • (1994) Artificial Intelligence Communications , vol.7 , Issue.1 , pp. 39-59
    • Aamodt, A.1    Plaza, E.2
  • 2
    • 26944456343 scopus 로고    scopus 로고
    • Learning to win: Case-based plan selection in a real-time strategy game
    • David Aha, Matthew Molineaux, and Marc Ponsen. Learning to win: Case-based plan selection in a real-time strategy game. In ICCBR, pages 5-20, 2005.
    • (2005) ICCBR , pp. 5-20
    • Aha, D.1    Molineaux, M.2    Ponsen, M.3
  • 3
    • 0026157412 scopus 로고
    • Outline for a theory of intelligence
    • DOI 10.1109/21.97471
    • J. Albus. Outline for a theory of intelligence. IEEE Transactions on Systems, Man, and Cybernetics, 21(3):473-509, 1991. (Pubitemid 21703526)
    • (1991) IEEE Transactions on Systems, Man and Cybernetics , vol.21 , Issue.3 , pp. 473-509
    • Albus, J.S.1
  • 5
    • 84880899286 scopus 로고    scopus 로고
    • Cbr for state value function approximation in reinforcement learning
    • Thomas Gabel and Martin Riedmiller. Cbr for state value function approximation in reinforcement learning. In ICCBR, 2005.
    • (2005) ICCBR
    • Gabel, T.1    Riedmiller, M.2
  • 10
    • 0031231885 scopus 로고    scopus 로고
    • Experiments with reinforcement learning in problems with continuous state and action spaces
    • Juan Santamaria, Richard Sutton, and Ashwin Ram. Experiments with reinforcement learning in problems with continuous state and action spaces. Adaptive Behavior, 6(2), 1998.
    • (1998) Adaptive Behavior , vol.6 , Issue.2
    • Santamaria, J.1    Sutton, R.2    Ram, A.3
  • 12
    • 33847202724 scopus 로고
    • Learning to predict by the methods of temporal difference
    • Richard Sutton. Learning to predict by the methods of temporal difference. Machine Learning, 3:9-44, 1988.
    • (1988) Machine Learning , vol.3 , pp. 9-44
    • Sutton, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.