• DocumentCode
    3507667
  • Title

    Swarms of Metaheuristic Agents: A Model for Collective intelligence

  • Author

    Aydin, Mehmet E. ; Wu, Joyce ; Zhang, Liang

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Univ. of Bedfordshire, Luton, UK
  • fYear
    2010
  • fDate
    4-6 Nov. 2010
  • Firstpage
    296
  • Lastpage
    301
  • Abstract
    Swarm intelligence algorithms are created to build collective intelligence based on inherent properties of populations. However, this sort of problem solving approaches use collective evolution of solutions, which make up the population relied on. Therefore the collective behaviour development is omitted. This paper addresses agentification of individuals forming up swarms, populations considered in problem solving using swarm intelligence algorithms. As each agentified individual will keep its own intelligence and use it in problem solving, the swarm intelligence algorithms used will be coordinating the agents and be supporting them in diversification of the search. This paper describes a framework of swarms of metaheuristic agents for problem solving and discusses the performance of particle swarm optimisation algorithms for purpose regarding the homogeneity in agents.
  • Keywords
    artificial intelligence; software agents; agent homogeneity; collective intelligence model; individual agentification; metaheuristic agents; swarm intelligence algorithms; collective intelligence; metaheuristic agents; particle swarm optimization; swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2010 International Conference on
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-1-4244-8538-3
  • Electronic_ISBN
    978-0-7695-4237-9
  • Type

    conf

  • DOI
    10.1109/3PGCIC.2010.49
  • Filename
    5662773