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Volumn 17, Issue 2, 2004, Pages 179-185

Multi-agent learning for routing control within an Internet environment

Author keywords

Internet control; Multi agent learning

Indexed keywords

COMPUTER NETWORKS; COMPUTER SIMULATION; CONTROL SYSTEMS; INTERNET; LEARNING SYSTEMS; PARALLEL PROCESSING SYSTEMS; ROUTERS; VIRTUAL REALITY;

EID: 2042544751     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2004.02.004     Document Type: Article
Times cited : (13)

References (10)
  • 1
    • 0024646143 scopus 로고
    • Learning to control an inverted pendulum using neural networks
    • Anderson, C.W., 1989. Learning to control an inverted pendulum using neural networks. IEEE Control Systems Magazine (4), 31-37.
    • (1989) IEEE Control Systems Magazine , Issue.4 , pp. 31-37
    • Anderson, C.W.1
  • 6
    • 34249831562 scopus 로고
    • Introduction: The challenge of reinforcement learning
    • Sutton, R.S., 1992. Introduction: the challenge of reinforcement learning. Machine Learning (8), 228.
    • (1992) Machine Learning , Issue.8 , pp. 228
    • Sutton, R.S.1
  • 7
    • 34249833101 scopus 로고
    • Technical note: Q-learning
    • Watkins, C., Dayan, P., 1992. Technical note: Q-learning. Machine Learning (8), 279.
    • (1992) Machine Learning , Issue.8 , pp. 279
    • Watkins, C.1    Dayan, P.2
  • 10
    • 0029346234 scopus 로고
    • Reinforcement learning control using interconnected learning automata
    • Wu, Q.H., 1995. Reinforcement learning control using interconnected learning automata. International Journal of Control (62), 1.
    • (1995) International Journal of Control , Issue.62 , pp. 1
    • Wu, Q.H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.