• DocumentCode
    2791621
  • Title

    Solvign multi-agent flexible planning problems based on soft constraints

  • Author

    Gu, Wen-xiang ; Wang, Jun-shu ; Yin, Ming-hao ; Li, Jin-li

  • Author_Institution
    Dept. of Comput. Sci., Northeast Normal Univ., Changchun
  • Volume
    4
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    2373
  • Lastpage
    2378
  • Abstract
    Multi-agent planning is an extension of classical artificial intelligence planning. Usually multiple agents can act together to achieve planning goal. But classical multi-agent methods require that the constraints are either totally satisfied or totally violated, which is too rigorous to formulate and to solve most of the real problems. In this paper, we define a multi-agent flexible planning problem which supports soft constraints, and then we present a new technique called distributed flexible constraint satisfaction (CSP), which is the combination of flexible CSP and distributed CSP, to deal with this planning problem. For a given multi-agent flexible planning problem, multiple agents can plan cooperatively with a satisfaction degree when solving the problem is difficult or infeasible, and then we can get a plan with a tradeoff between plan quality and length.
  • Keywords
    constraint theory; multi-agent systems; planning (artificial intelligence); artificial intelligence planning; distributed flexible constraint satisfaction; multi agent flexible planning problem; soft constraint; Artificial intelligence; Computer science; Cost function; Cybernetics; Electronic commerce; Job shop scheduling; Machine learning; Privacy; Robot kinematics; Supply chain management; Distributed flexible CSP; Multi-agent flexible planning; Multi-agent planning; Soft constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620802
  • Filename
    4620802