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Volumn , Issue , 2005, Pages 233-240

Multi-agent reward analysis for learning in noisy domains

Author keywords

Multiagent Systems; Reinforcement Learning; Visualization

Indexed keywords

AUTONOMOUS AGENTS; COMPUTER SIMULATION; LEARNING SYSTEMS; PROBLEM SOLVING; VISUALIZATION;

EID: 33644813420     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (10)

References (23)
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    • Crites, R.H.1    Barto, A.G.2
  • 9
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    • Hinton, G.1
  • 12
    • 0002218603 scopus 로고    scopus 로고
    • Coordination and learning in multi-robot systems
    • March
    • Maja J Mataric. Coordination and learning in multi-robot systems. In IEEE Intelligent Systems, pages 6-8, March 1998.
    • (1998) IEEE Intelligent Systems , pp. 6-8
    • Mataric, M.J.1
  • 14
    • 51649111071 scopus 로고    scopus 로고
    • Designing agent utilities for coordinated, scalable and robust multi-agent systems
    • P. Scerri, R. Mailler, and R. Vincent, editors, Springer. to appear
    • K. Tumer. Designing agent utilities for coordinated, scalable and robust multi-agent systems. In P. Scerri, R. Mailler, and R. Vincent, editors, Challenges in the Coordination of Large Scale Multiagent Sy stems. Springer, 2005. to appear.
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    • Tumer, K.1
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    • Wolpert, D.H.1    Tumer, K.2
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    • Improving search algorithms by using intelligent coordinates
    • D. H. Wolpert, K. Tumer, and E. Bandari. Improving search algorithms by using intelligent coordinates. Physical Review E, 69:017701, 2004.
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    • Wolpert, D.H.1    Tumer, K.2    Bandari, E.3
  • 23
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    • Collective intelligence for control of distributed dynamical systems
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    • D. H. Wolpert, K. Wheeler, and K. Tumer. Collective intelligence for control of distributed dynamical systems. Europhysics Letters, 49(6), March 2000.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.