메뉴 건너뛰기




Volumn 2, Issue , 2011, Pages 897-904

Distributed model shaping for scaling to decentralized POMDPs with hundreds of agents

Author keywords

DEC POMDP; Multi agent systems; Uncertainty

Indexed keywords

ALGORITHMS; AUTONOMOUS AGENTS; MULTI AGENT SYSTEMS;

EID: 84899454751     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (38)

References (13)
  • 1
    • 27344432831 scopus 로고    scopus 로고
    • Solving transition independent decentralized Markov decision processes
    • December
    • R. Becker, S. Zilberstein, V. Lesser, and C. V. Goldman. Solving transition independent decentralized Markov decision processes. JAIR, 22:423-455, December 2004.
    • (2004) JAIR , vol.22 , pp. 423-455
    • Becker, R.1    Zilberstein, S.2    Lesser, V.3    Goldman, C.V.4
  • 2
    • 0036874366 scopus 로고    scopus 로고
    • The complexity of decentralized control of Markov decision processes
    • D. S. Bernstein, R. Givan, N. Immerman, and S. Zilberstein. The complexity of decentralized control of Markov decision processes. Math. Oper. Res., 27(4):819-840, 2002.
    • (2002) Math. Oper. Res , vol.27 , Issue.4 , pp. 819-840
    • Bernstein, D.S.1    Givan, R.2    Immerman, N.3    Zilberstein, S.4
  • 3
    • 0345327609 scopus 로고    scopus 로고
    • Multi-robot task allocation: Analyzing the complexity and optimality of key architectures
    • B. Gerkey and M. Mataric. Multi-robot task allocation: Analyzing the complexity and optimality of key architectures. In ICRA, 2003.
    • (2003) ICRA
    • Gerkey, B.1    Mataric, M.2
  • 4
    • 0036832951 scopus 로고    scopus 로고
    • A sparse sampling algorithm for near-optimal planning in large Markov decision processes
    • M. Kearns, Y. Mansour, and A. Y. Ng. A sparse sampling algorithm for near-optimal planning in large Markov decision processes. Machine Learning, 49(2-3):193-208, 2002.
    • (2002) Machine Learning , vol.49 , Issue.2-3 , pp. 193-208
    • Kearns, M.1    Mansour, Y.2    Ng, A.Y.3
  • 5
    • 84899448600 scopus 로고    scopus 로고
    • Exploiting coordination locales in distributed POMDPs via social model shaping
    • J. Marecki, T. Gupta, P. Varakantham, M. Yokoo, and M. Tambe. Exploiting coordination locales in distributed POMDPs via social model shaping. In ICAPS, 2009.
    • (2009) ICAPS
    • Marecki, J.1    Gupta, T.2    Varakantham, P.3    Yokoo, M.4    Tambe, M.5
  • 6
    • 34247214638 scopus 로고    scopus 로고
    • Networked distributed pomdps: A synthesis of distributed constraint optimization and POMDPs
    • R. Nair, P. Varakantham, M. Tambe, and M. Yokoo. Networked distributed pomdps: A synthesis of distributed constraint optimization and POMDPs. In AAAI, 2005.
    • (2005) AAAI
    • Nair, R.1    Varakantham, P.2    Tambe, M.3    Yokoo, M.4
  • 8
    • 37149021584 scopus 로고    scopus 로고
    • A scalable, distributed algorithm for efficient task allocation
    • P. V. Sander, D. Peleshchuk, and B. J. Grosz. A scalable, distributed algorithm for efficient task allocation. In AAMAS, 2002.
    • (2002) AAMAS
    • Sander, P.V.1    Peleshchuk, D.2    Grosz, B.J.3
  • 10
    • 51649085567 scopus 로고    scopus 로고
    • Improved memory-bounded dynamic programming for decentralized POMDPs
    • S. Seuken and S. Zilberstein. Improved memory-bounded dynamic programming for decentralized POMDPs. In UAI, 2007.
    • (2007) UAI
    • Seuken, S.1    Zilberstein, S.2
  • 12
    • 33644814996 scopus 로고    scopus 로고
    • Exploiting belief bounds: Practical POMDPs for personal assistant agents
    • P. Varakantham, R. Maheswaran, and M. Tambe. Exploiting belief bounds: Practical POMDPs for personal assistant agents. In AAMAS, 2005.
    • (2005) AAMAS
    • Varakantham, P.1    Maheswaran, R.2    Tambe, M.3
  • 13
    • 10044270060 scopus 로고    scopus 로고
    • Distributed stochastic search and distributed breakout: Properties, comparison and applications to constraint optimization problems in sensor networks
    • W. Zhang, G. Wang, Z. Xing, and L. Wittenburg. Distributed stochastic search and distributed breakout: properties, comparison and applications to constraint optimization problems in sensor networks. Artificial Intelligence, 161(1-2):55-87, 2005.
    • (2005) Artificial Intelligence , vol.161 , Issue.1-2 , pp. 55-87
    • Zhang, W.1    Wang, G.2    Xing, Z.3    Wittenburg, L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.