• DocumentCode
    3088529
  • Title

    Co-evolving semi-competitive interactions of sheepdog herding behaviors utilizing a simple rule-based multi agent framework

  • Author

    Lakshika, Erandi ; Barlow, Michael ; Easton, Adam

  • Author_Institution
    Sch. of Eng. & IT, Univ. of New South Wales, Canberra, ACT, Australia
  • fYear
    2013
  • fDate
    16-19 April 2013
  • Firstpage
    82
  • Lastpage
    89
  • Abstract
    Sheepdog herding behaviors demonstrate an interesting form of interactions between two classes of agents - sheep and the dog. The nature of the interactions between sheep and the dog takes a special form of competition which is different to the traditional prey-predator interactions where the success of prey depends on the failure of the predator and vice versa. In consequent, the development of an appropriate objective function to efficiently co-evolve successful sheepdog herding behaviors becomes challenging. This paper presents a framework to efficiently co-evolve sheepdog herding behaviors utilizing the simple rule based agent approach in order to derive high fidelity behavior dynamics and discusses the challenges involved in the process.
  • Keywords
    knowledge based systems; multi-agent systems; optimisation; prey-predator interactions; rule-based multiagent framework; semicompetitive interactions coevolution; sheepdog herding behaviors; Complexity theory; Dynamics; Linear programming; Robots; Sociology; Space exploration; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Life (ALIFE), 2013 IEEE Symposium on
  • Conference_Location
    Singapore
  • ISSN
    2160-6374
  • Type

    conf

  • DOI
    10.1109/ALIFE.2013.6602435
  • Filename
    6602435