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Volumn 8, Issue 2, 2000, Pages 167-185

Directing genetic algorithms for probabilistic reasoning through reinforcement learning

Author keywords

Belief revision; Genetic algorithm; Probabilistic reasoning; Reinforcement learning

Indexed keywords


EID: 0242682342     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488500000125     Document Type: Article
Times cited : (4)

References (18)
  • 1
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    • Gregory F. Cooper. The computational complexity of probabilistic inference using bayesian networks. Artificial Intelligence, 42:393-405, 1990.
    • (1990) Artificial Intelligence , vol.42 , pp. 393-405
    • Cooper, G.F.1
  • 2
    • 0031361611 scopus 로고    scopus 로고
    • Machine learning research: Four current directions
    • T. G. Dietterich. Machine learning research: Four current directions. AI Magazine, 18:97-136, 1997.
    • (1997) AI Magazine , vol.18 , pp. 97-136
    • Dietterich, T.G.1
  • 6
    • 0346129895 scopus 로고    scopus 로고
    • Belief network inference algorithms: A study of performance based on domain characterisation
    • Monash University, Clayton, VIC, 3168 Australia
    • N. Jitnah and A.E.Nicholson. Belief network inference algorithms: a study of performance based on domain characterisation. Technical Report TR-96-249, Monash University, Clayton, VIC, 3168 Australia, 1996.
    • (1996) Technical Report TR-96-249
    • Jitnah, N.1    Nicholson, A.E.2
  • 10
    • 0006214312 scopus 로고
    • GALGO: A Genetic ALGOrithm decision support tool for complex uncertain systems modeled with bayesian belief networks
    • Carlos Rojas-Guzman and Mark A. Kramer. GALGO: A Genetic ALGOrithm decision support tool for complex uncertain systems modeled with bayesian belief networks. In Proceedings of the Conference on Uncertainty in Artificial Intelligence, pages 368-375, 1993.
    • (1993) Proceedings of the Conference on Uncertainty in Artificial Intelligence , pp. 368-375
    • Rojas-Guzman, C.1    Kramer, M.A.2
  • 14
    • 0028483915 scopus 로고
    • Finding MAPs for belief networks is NP-hard
    • Solomon E. Shimony. Finding MAPs for belief networks is NP-hard. Artificial Intelligence, 68:399-410, 1994.
    • (1994) Artificial Intelligence , vol.68 , pp. 399-410
    • Shimony, S.E.1
  • 18
    • 0006370953 scopus 로고    scopus 로고
    • Probabilistic reasonging through genetic algorithms and reinforcement learning
    • X. Zhong and E. Santos Jr. Probabilistic reasonging through genetic algorithms and reinforcement learning. In The 12th International FLAIRS conference, pages 477-481, 1999.
    • (1999) The 12th International FLAIRS Conference , pp. 477-481
    • Zhong, X.1    Santos Jr., E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.