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Extending Answer Sets for Logic Programming Agents

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Abstract

We present systems of logic programming agents (LPAS) to model the interactions between decision-makers while evolving to a conclusion. Such a system consists of a number of agents connected by means of unidirectional communication channels. Agents communicate with each other by passing answer sets obtained by updating the information received from connected agents with their own private information. We introduce a credulous answer set semantics for logic programming agents. As an application, we show how extensive games with perfect information can be conveniently represented as logic programming agent systems, where each agent embodies the reasoning of a game player, such that the equilibria of the game correspond with the semantics agreed upon by the agents in the LPAS.

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References

  1. S. Abramsky and C.-H.L. Ong, Full abstraction in the lazy lambda calculus, Information and Computation 105(2) (1993) 159–276.

    Google Scholar 

  2. J.J. Alferes, J.A. Leite, L.M. Pereira, H. Przymusinska and T.C. Przymusinski, Dynamic logic programming, in: [7] pp. 98–111.

    Google Scholar 

  3. J.J. Alferes and L.M. Pereira, Updates plus preferences, in: Proceedings of the Logic in Artificial Intelligence (JELIA2000) Workshop, Malaga, Spain, Lecture Notes in Artificial Intelligence, Vol. 1919 (2000) pp. 345–360.

  4. G. Brewka, Well-founded semantics for extended logic programs with dynamic preferences, Journal of Artificial Intelligence Research 4 (1996) 19–36.

    Google Scholar 

  5. F. Buccafurri, W. Faber and N. Leone, Disjunctive logic programs with inheritance, in: International Conference on Logic Programming (ICLP), Las Cruces, NM, ed. D. De Schreye (1999) pp. 79–93.

  6. F. Buccafurri, N. Leone and P. Rullo, Disjunctive ordered logic: Semantics and expressiveness, in:[7] pp. 418–431.

    Google Scholar 

  7. A.G. Cohn, L.K. Schubert and S.C. Shapiro (eds.), Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning (Morgan Kaufmann, Trento, 1998).

    Google Scholar 

  8. [8] M. De Vos, Implementing ordered choice logic programs, in preparation.

  9. M. De Vos and D. Vermeir, Choice logic programs and nash equilibria in strategic games, in: Computer Science Logic (CSL'99), Madrid, Spain, eds. J. Flum and M. Rodríguez-Artalejo, Lecture Notes in Computer Science, Vol. 1683 (1999) pp. 266–276.

  10. M. De Vos and D. Vermeir, On the role of negation in choice logic programs, in: Logic Programming and Non-Monotonic Reasoning Conference (LPNMR'99), El Paso, TX, eds. M. Gelfond, N. Leone and G. Pfeifer, Lecture Notes in Artificial Intelligence, Vol. 1730 (1999) pp. 236–246.

  11. M. De Vos and D. Vermeir: A logic for modelling decision making with dynamic preferences, in: Proceedings of the Logic in Artificial Intelligence (JELIA2000) Workshop, Malaga, Spain, Lecture Notes in Artificial Intelligence, Vol. 1919 (2000) pp. 391–406.

  12. M. De Vos and D. Vermeir, Logic programming agents and game theory, in: Answer Set Programming: Towards Efficient and Scalable Knowledge Representation and Reasoning, Papers from 2001 AAAI Spring Symposium, Cochairs A. Provetti and T.C. Son (AAAI Press, Palo Alto, CA, 2001) pp. 27–33.

    Google Scholar 

  13. M. De Vos and D. Vermeir, Dynamic decision making in logic programming and game theory, in: AI2002: Advances in Artificial Intelligence (2002) pp. 36–47.

  14. J. Delgrande, T. Schaub and H. Tompits, Logic programs with compiled preferences, in: European Conference on Artificial Intelligence, ed. W. Horn (2000) pp. 392–398.

  15. T. Eiter, M. Fink, G. Sabbatini and H. Tompits, On properties of update sequences based on causal rejection, Theory and Practice of Logic Programming 2(6) (2002).

  16. T. Eiter, N. Leone, C. Mateis, G. Pfeifer and F. Scarcello, The KR system dlv: Progress Report, comparisons and benchmarks, in: KR'98: Principles of Knowledge Representation and Reasoning, eds. A.G. Cohn, L. Schubert and S.C. Shapiro (Morgan Kaufmann, San Francisco, CA, 1998) pp. 406–417.

    Google Scholar 

  17. D. Gabbay, E. Laenens and D. Vermeir, Credulous vs. sceptical semantics for ordered logic programs, in: Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning, eds. J. Allen, R. Fikes and E. Sandewall (The MIT Press, Cambridge, MA, 1991) pp. 208–217.

    Google Scholar 

  18. E. Laenens and D. Vermeir, A universal fixpoint semantics for ordered logic, Computers and Artificial Intelligence 19(3) (2000).

  19. V. Lifschitz, Answer set programming and plan generation, Journal of Artificial Intelligence 138(1-2) (2002) 39–54.

    Google Scholar 

  20. I. Niemelä and P. Simons, Smodels: An implementation of the stable model and well-founded semantics for normal LP, in: Proceedings of the 4th International Conference on Logic Programing and Nonmonotonic Reasoning, eds. J. Dix, U. Furbach and A. Nerode, Lecture Notes in Artificial Intelligence, Vol. 1265 (Springer, Berlin, 1997) pp. 420–429.

    Google Scholar 

  21. S. Olafsson, Resource allocation as an evolving strategy, Evolutionary Computation 4(1) (1996) 32–54.

    Google Scholar 

  22. M.J. Osborne and A. Rubinstein, A Course in Game Theory, 3rd edn. (The MIT Press, Cambridge, MA, 1996).

    Google Scholar 

  23. D. Poole, The independent choice logic for modelling multiple agents under uncertainty, Artificial Intelligence 94(1-2) (1997) 7–56.

    Google Scholar 

  24. J.S. Rosenschein and G. Zlotkin, Rules of Encounter. Designing Conventions for Automated Negotiation among Computers (The MIT Press, Cambridge, MA, 1994).

    Google Scholar 

  25. C. Sakama and K. Inoue, Representing priorities in logic programs, in: Proceedings of the 1996 Joint International Conference and Symposium on Logic Programming, ed. M. Maher (Cambridge, 1996) pp. 82–96.

  26. J. Von Neumann and O. Morgenstern, Theory of Games and Economic Behavior (Wiley, New York, 1944).

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, University of Bath, Bath, BA2 7AY, United Kingdom

    M. De Vos

  2. Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussel, Belgium

    D. Vermeir

Authors
  1. M. De Vos
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  2. D. Vermeir
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De Vos, M., Vermeir, D. Extending Answer Sets for Logic Programming Agents. Annals of Mathematics and Artificial Intelligence 42, 103–139 (2004). https://doi.org/10.1023/B:AMAI.0000034524.89865.d2

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  • DOI: https://doi.org/10.1023/B:AMAI.0000034524.89865.d2

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