• DocumentCode
    480804
  • Title

    Negotiation in Semi-cooperative Agreement Problems

  • Author

    Crawford, Elisabeth ; Veloso, Manuela

  • Author_Institution
    Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA
  • Volume
    2
  • fYear
    2008
  • fDate
    9-12 Dec. 2008
  • Firstpage
    252
  • Lastpage
    258
  • Abstract
    In this paper we introduce the Semi-Cooperative Extended Incremental Multiagent Agreement Problem with Preferences (SC-EIMAPP). In SC-EIMAPPs, variables arise over time. For each variable, a set of distributed agents gain utility for agreeing on an option to assign to the variable. We define semi-cooperative utility as an agent´s privately owned preferences, discounted as negotiation time increases. SC-EIMAPPs reflect real world agreement problems, including meeting scheduling and task allocation.We analyze negotiation in SC-EIMAPPs theoretically. We note that agents necessarily reveal information about their own preferences and constraints as they negotiate agreements. We show how agents can use this limited and noisy information to learn to negotiate more effectively. We demonstrate our results experimentally.
  • Keywords
    learning (artificial intelligence); multi-agent systems; scheduling; distributed agent gain utility; meeting scheduling; negotiation learning; semicooperative extended incremental multiagent agreement problem; task allocation; Bayesian methods; Collaboration; Computer science; Game theory; Humans; Intelligent agent; Meeting planning; Proposals; Protocols; USA Councils; Multiagent Learning; Negotiation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-0-7695-3496-1
  • Type

    conf

  • DOI
    10.1109/WIIAT.2008.417
  • Filename
    4740629