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Volumn 17, Issue 2, 2008, Pages 320-338

Analyzing and visualizing multiagent rewards in dynamic and stochastic domains

Author keywords

Multiagent learning; Reinforcement learning; Reward analysis; Visualization

Indexed keywords


EID: 51649111408     PISSN: 13872532     EISSN: 15737454     Source Type: Journal    
DOI: 10.1007/s10458-008-9046-9     Document Type: Article
Times cited : (121)

References (32)
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    • Stone P. and Veloso M. (2000). Multiagent systems: A survey from a machine learning perspective. Autonomous Robots 8(3): 345-383
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    • Stone, P.1    Veloso, M.2
  • 24
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    • Designing agent utilities for coordinated, scalable and robust multi-agent systems
    • Scerri, P. Mailler, R., & R. Vincent (Eds.) Springer (to appear)
    • Tumer, K. (2005). Designing agent utilities for coordinated, scalable and robust multi-agent systems. In Scerri, P. Mailler, R., & R. Vincent (Eds.), Challenges in the coordination of large scale multiagent Systems. Springer (to appear).
    • (2005) Challenges in the Coordination of Large Scale Multiagent Systems
    • Tumer, K.1
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    • Optimal payoff functions for members of collectives
    • 2/3
    • Wolpert D.H. and Tumer K. (2001). Optimal payoff functions for members of collectives. Advances in Complex Systems 4(2/3): 265-279
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    • Wolpert, D.H.1    Tumer, K.2
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    • Improving search algorithms by using intelligent coordinates
    • Wolpert D.H., Tumer K. and Bandari E. (2004). Improving search algorithms by using intelligent coordinates. Physical Review E 69: 017701
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    • Wolpert, D.H.1    Tumer, K.2    Bandari, E.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.