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The Spider Model of Agents

  • Freeman Y. Huang
  • David B. Skillicorn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2164)

Abstract

We take the position that large-scale distributed systems are better understood, at all levels, when locality is taken into account. When communication and mobility are clearly separated, it is easier to design, understand, and implement goal-directed agent programs. We present the Spider model of agents to validate our position. Systems contain two kinds of entities: spiders which represent service providers, and arms, which represent goal-directed agents. Communication, however, takes place only between an arm and the spider at which it is currently located. We present both a formal description of the model using the ambient calculus, and a Java-based implementation.

Keywords

agent models ambient calculus mobile agents locality formal reasoning Java 

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References

  1. 1.
    P. S. K. Booker, R. K. Granger, E. J. Guest, S. A. Norton, J. E. Price, and H. Glaser. Software agents and their use in mobile computing. Technical Report DSSE-TR-99-5, Declarative Systems and Software Engineering Group, University of Southampton, February 1999.Google Scholar
  2. 2.
    G. Cabri, L. Leonardi, and F. Zambonelli. MARS: A Programmable Coordination Architecture for Mobile Agents. IEEE Internet Computing, 4(4):26–35, 2000.CrossRefGoogle Scholar
  3. 3.
    Luca Cardelli and Andrew D. Gordon. Mobile ambients. In M. Nivat, editor, Proceedings of Foundations of Software Science and Computation Structures (FoSSaCS), volume 1378, pages 140–155. Springer-Verlag, Berlin, Germany, 1998.CrossRefGoogle Scholar
  4. 4.
    Neeran M. Karnik and Anand R. Tripathi. Design issues in mobile-agent programming systems. IEEE Concurrency, 6(3):52–61, 1998.CrossRefGoogle Scholar
  5. 5.
    Danny B. Lange. Java Aglet Application Programming Interface White Paper. IBM Tokyo Research Lab, February 1997. Online: http://www.trl.ibm.com/aglets/JAAPI-whitepaper.html.
  6. 6.
    Francesca Levi and Davide Sangiorgi. Controlling interference in ambients. In Symposium on Principles of Programming Languages, pages 352–364, 2000.Google Scholar
  7. 7.
    M. J. Wooldridge. The Logical Modelling of Computational Multi-Agent Systems. PhD thesis, University of Manchester, Manchester, UK, 1992.Google Scholar
  8. 8.
    M. J. Wooldridge and N. R. Jennings. Intelligent agents: Theory and practice. The Knowledge Engineering Review, 10(2):115–152, 1995.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Freeman Y. Huang
    • 1
  • David B. Skillicorn
    • 1
  1. 1.Department of Computing and Information ScienceQueen’s UniversityKingstonCanada

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