• DocumentCode
    777914
  • Title

    Biotope: an integrated framework for simulating distributed multiagent computational systems

  • Author

    Symeonidis, Andreas L. ; Valtos, Evangelos ; Seroglou, Seraphim ; Mitkas, Pericles A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Greece
  • Volume
    35
  • Issue
    3
  • fYear
    2005
  • fDate
    5/1/2005 12:00:00 AM
  • Firstpage
    420
  • Lastpage
    432
  • Abstract
    The study of distributed computational systems issues, such as heterogeneity, concurrency, control, and coordination, has yielded a number of models and architectures, which aspire to provide satisfying solutions to each of the above problems. One of the most intriguing and complex classes of distributed systems are computational ecosystems, which add an "ecological" perspective to these issues and introduce the characteristic of self-organization. Extending previous research work on self-organizing communities, we have developed Biotope, which is an agent simulation framework, where each one of its members is dynamic and self-maintaining. The system provides a highly configurable interface for modeling various environments as well as the "living" or computational entities that reside in them, while it introduces a series of tools for monitoring system evolution. Classifier systems and genetic algorithms have been employed for agent learning, while the dispersal distance theory has been adopted for agent replication. The framework has been used for the development of a characteristic demonstrator, where Biotope agents are engaged in well-known vital activities-nutrition, communication, growth, death-directed toward their own self-replication, just like in natural environments. This paper presents an analytical overview of the work conducted and concludes with a methodology for simulating distributed multiagent computational systems.
  • Keywords
    distributed processing; multi-agent systems; self-adjusting systems; Biotope agent simulation framework; agent learning; agent replication; classifier systems; computational ecosystems; dispersal distance theory; distributed multiagent computational system simulation; genetic algorithms; integrated framework; system evolution monitoring; Analytical models; Biological system modeling; Computational modeling; Computer architecture; Computer interfaces; Concurrent computing; Distributed computing; Ecosystems; Genetic algorithms; Monitoring; Classifier systems; computational ecosystems; distributed systems; genetic algorithms (GAs); self-organization;
  • fLanguage
    English
  • Journal_Title
    Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4427
  • Type

    jour

  • DOI
    10.1109/TSMCA.2005.846406
  • Filename
    1420670