• DocumentCode
    3178613
  • Title

    Foraging theory for decision-making system design: task-type choice

  • Author

    Andrews, Burton W. ; Passino, Kevin M. ; Waite, Thomas A.

  • Author_Institution
    Dept. Electr. & Comput. Eng., Ohio State Univ., Columbus, OH, USA
  • Volume
    5
  • fYear
    2004
  • fDate
    14-17 Dec. 2004
  • Firstpage
    4740
  • Abstract
    Foraging theory is typically used to model animal decision making. We describe an agent such as an autonomous vehicle or software module as a forager searching for tasks. The prey model is used to predict which types of tasks an agent should choose to maximize its rate of reward. We expand and apply these concepts to fit an autonomous vehicle control problem and to provide insight into how to make high-level control decisions. We also discuss extensions of the basic prey model, showing how a risk-sensitive version can be used to alter policies when time or fuel is limited. Throughout the applications, we examine ways an agent can estimate environmental parameters when such parameters are not known.
  • Keywords
    decision making; ecology; mobile robots; autonomous vehicle control problem; decision-making system design; environmental parameters estimation; foraging theory; high-level control decisions; prey model; risk-sensitivity; software module; task-type choice; Animals; Automotive engineering; Biological system modeling; Biology computing; Control systems; Decision making; Environmental factors; Evolution (biology); Mobile robots; Remotely operated vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2004. CDC. 43rd IEEE Conference on
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-8682-5
  • Type

    conf

  • DOI
    10.1109/CDC.2004.1429539
  • Filename
    1429539