LAIMA: A Multi-agent Platform Using Ordered Choice Logic Programming

  • Marina De Vos
  • Tom Crick
  • Julian Padget
  • Martin Brain
  • Owen Cliffe
  • Jonathan Needham
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3904)

Abstract

Multi-agent systems (MAS) can take many forms depending on the characteristics of the agents populating them. Amongst the more demanding properties with respect to the design and implementation of multi-agent system is how these agents may individually reason and communicate about their knowledge and beliefs, with a view to cooperation and collaboration. In this paper, we present a deductive reasoning multi-agent platform using an extension of answer set programming (ASP). We show that it is capable of dealing with the specification and implementation of the system’s architecture, communication and the individual agent’s reasoning capacities. Agents are represented as Ordered Choice Logic Programs (OCLP) as a way of modelling their knowledge and reasoning capacities, with communication between the agents regulated by uni-directional channels transporting information based on their answer sets. In the implementation of our system we combine the extensibility of the JADE framework with the flexibility of the OCT front-end to the Smodels answer set solver. The power of this approach is demonstrated by a multi-agent system reasoning about equilibria of extensive games with perfect information.

Keywords

Nash Equilibrium Logic Program Logic Programming Choice Rule Extensive Game 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. 1.
    Opencyc, http://www.cyc.com.opencyc Google Scholar
  2. 2.
    Baral, C.: Knowledge Representation, Reasoning and Declarative Problem Solving. Cambridge Press, New York (2003)CrossRefMATHGoogle Scholar
  3. 3.
    Brain, M., De Vos, M.: Implementing OCLP as a front-end for Answer Set Solvers: From Theory to Practice. In: ASP 2003: Answer Set Programming: Advances in Theory and Implementation, Ceur-WS (2003), CEUR-WS.org/Vol-78/asp03-final-brain.ps
  4. 4.
    Osborne, M.J., Rubinstein, A.: A Course in Game Theory, 3rd edn. The MIT Press, Cambridge (1996)MATHGoogle Scholar
  5. 5.
  6. 6.
  7. 7.
    De Vos, M.: Implementing Ordered Choice Logic Programming using Answer Set Solvers. In: Seipel, D., Turull-Torres, J.M.a. (eds.) FoIKS 2004. LNCS, vol. 2942, pp. 59–77. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    De Vos, M., Vermeir, D.: Extending Answer Sets for Logic Programming Agents. Annals of Mathematics and Artifical Intelligence 42, 103–139 (2004); Special Issue on Computational Logic in Multi-Agent SystemsMathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Denecker, M.: What’s in a Model? Epistemological Analysis of Logic Programming (2003), CEUR-WS.org/Vol-78/
  10. 10.
    De Vos, M., Vermeir, D.: On the Role of Negation in Choice Logic Programs. In: Gelfond, M., Leone, N., Pfeifer, G. (eds.) LPNMR 1999. LNCS (LNAI), vol. 1730, pp. 236–246. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  11. 11.
    Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Proc. of fifth logic programming symposium, pp. 1070–1080. MIT Press, Cambridge (1988)Google Scholar
  12. 12.
    Niemelä, I., Simons, P.: Smodels: An implementation of the stable model and well-founded semantics for normal LP. In: Fuhrbach, U., Dix, J., Nerode, A. (eds.) LPNMR 1997. LNCS(LNAI), vol. 1265, pp. 420–429. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  13. 13.
    Eiter, T., Leone, N., Mateis, C., Pfeifer, G., Scarcello, F.: The KR system dlv: Progress report, comparisons and benchmarks. In: Cohn, A.G., Schubert, L., Shapiro, S.C. (eds.) KR 1998: Principles of Knowledge Representation and Reasoning, pp. 406–417. Morgan Kaufmann, San Francisco (1998)Google Scholar
  14. 14.
  15. 15.
    Wooldridge, M., Jennings, N.R., Kinny, D.: The gaia methodology for agent-oriented analysis and design. Autonomous Agents and Multi-Agent Systems 3, 285–312 (2000)CrossRefGoogle Scholar
  16. 16.
    Dix, J., Eiter, T., Fink, M., Polleres, A., Zhang, Y.: Monitoring Agents using Declarative Planning. In: Günter, A., Kruse, R., Neumann, B. (eds.) KI 2003. LNCS (LNAI), vol. 2821, pp. 345–370. Springer, Heidelberg (2003)Google Scholar
  17. 17.
    Nogueira, M., Balduccini, M., Gelfond, M., Watson, R., Barry, M.: A A-Prolog Decision Support System for the Space Shuttle. In: Answer Set Programming: Towards Efficient and Scalable Knowledge Represenation and Reasoning. American Association for Artificial Intelligence Press, Stanford, Palo Alto (2001)Google Scholar
  18. 18.
    Gelfond, M.: Answer set programming and the design of deliberative agents. In: Demoen, B., Lifschitz, V. (eds.) ICLP 2004. LNCS, vol. 3132, pp. 19–26. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  19. 19.
    Leite, J.A., Alferes, J.J., Pereira, L.M.: Minerva - a dynamic logic programming agent architecture. In: Meyer, J.J., Tambe, M. (eds.) Intelligent Agents VIII. LNCS (LNAI), vol. 2002, pp. 141–157. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  20. 20.
    Wooldridge, M.J., Jennings, N.R.: Agent theories, architectures and languages: a survey. In: Wooldridge, M.J., Jennings, N.R. (eds.) ECAI 1994 and ATAL 1994. LNCS (LNAI), vol. 890, pp. 1–39. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  21. 21.
    Costantini, S., Tocchio, A.: A Logic Programming Language for Multi-agent Systems. In: Flesca, S., Greco, S., Leone, N., Ianni, G. (eds.) JELIA 2002. LNCS (LNAI), vol. 2424, p. 1. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  22. 22.
    Kakas, A., Mancarella, P., Sadri, F., Stathis, K., Toni, F.: Declarative agent control. In: Leite, J., Torroni, P. (eds.) 5thWorkshop on Computational Logic inMulti-Agent Systems, CLIMAV (2004)Google Scholar
  23. 23.
  24. 24.
    Jørring, U., Scherlis, W.: Compilers and staging transformations. In: Proceedings of 13th ACM Symposium on Principles of Programming Languages, pp. 86–96. ACM, New York (1986)Google Scholar
  25. 25.
    Brain, M.J.: Undergraduate dissertation: Incremental answer set programming. Technical Report 2004–05, University of Bath, U.K., Bath (2004)Google Scholar
  26. 26.
    Ciampolini, A., Torroni, P.: Using abductive logic agents for modeling the judicial evaluation of crimimal evidence. Applied Artificial Intelligence 18, 251–275 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Marina De Vos
    • 1
  • Tom Crick
    • 1
  • Julian Padget
    • 1
  • Martin Brain
    • 1
  • Owen Cliffe
    • 1
  • Jonathan Needham
    • 1
  1. 1.Department of Computer ScienceUniversity of BathBathUK

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