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Volumn 20, Issue 6 SPEC. ISS., 2004, Pages 553-562

Learning policies for single machine job dispatching

Author keywords

Dispatching rule selection; Q learning algorithm; Reinforcement learning

Indexed keywords

DECISION MAKING; FUNCTIONS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MULTI AGENT SYSTEMS; SCHEDULING; SOFTWARE AGENTS;

EID: 4944253466     PISSN: 07365845     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rcim.2004.07.003     Document Type: Conference Paper
Times cited : (38)

References (20)
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    • Solving semi-Markov decision problems using average reward reinforcement learning
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    • Das, T.K.1    Gosavi, A.2    Mahadevan, S.3    Marchalleck, N.4
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    • Intelligent dynamic control policies for serial production lines
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    • (2001) IIE Trans , vol.33 , pp. 65-77
    • Paternina-Arboleda, C.D.1    Das, T.K.2
  • 13
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    • Dynamic job-shop scheduling using reinforcement learning agents
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    • (2000) Robotics Autonomous Systems , vol.33 , pp. 169-178
    • Aydin, M.E.1    Oztemel, E.2
  • 14
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    • Temporal difference learning and TD-Gammon
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  • 17
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    • Generalization in Reinforcement learning: Successful examples using spare coarse coding
    • Touretzky DS, Mozer MC, Hasselmo ME, editors. Cambridge, MA: MIT Press
    • Sutton RS. Generalization in Reinforcement learning: successful examples using spare coarse coding. In: Touretzky DS, Mozer MC, Hasselmo ME, editors. Advances in neural information processing systems: proceedings of the 1995 conference. Cambridge, MA: MIT Press; 1996. p. 1038-44.
    • (1996) Advances in Neural Information Processing Systems: Proceedings of the 1995 Conference , pp. 1038-1044
    • Sutton, R.S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.