• DocumentCode
    2442798
  • Title

    Identifying Optimal Jobs to Work On: The Role of Attitude in Job Selection

  • Author

    Ahn, Jaesuk ; Jones, Chris L D ; Barber, K. Suzanne

  • Author_Institution
    Univ. of Texas at Austin, Austin
  • fYear
    2007
  • fDate
    2-5 Nov. 2007
  • Firstpage
    356
  • Lastpage
    362
  • Abstract
    In this paper, the meaning of attitude and its role in an agent´s job selection behavior is discussed. When agents build teams, a critical step in improving performance is choosing which jobs to work on in the context of both changing environmental conditions and other agents´ uncertain behaviors. This research introduces a decision theoretic model and the concept of attitude, and provides methods to incorporate different possible attitudes in constructing an expected utility function to guide agents in ranking potential jobs. In this way, attitudes define how an agent prioritizes different possible job choices. Three types of attitudes are defined: attitudes toward proactive behavior, potential risk, and reward. The paper shows that agents using the presented model are able to increase their payoff by identifying optimal jobs under different environmental conditions with varied parameters.
  • Keywords
    multi-agent systems; utility theory; agent job selection behavior; agents attitude model; decision theoretic model; expected utility function; multi agent system; Decision making; Equations; IP networks; Intelligent agent; Intelligent systems; Laboratories; Mobile agents; Multiagent systems; USA Councils; Utility theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Agent Technology, 2007. IAT '07. IEEE/WIC/ACM International Conference on
  • Conference_Location
    Fremont, CA
  • Print_ISBN
    978-0-7695-3027-7
  • Type

    conf

  • DOI
    10.1109/IAT.2007.76
  • Filename
    4407310