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Solving Conflicting Beliefs with a Distributed Belief Revision Approach

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Advances in Artificial Intelligence (IBERAMIA 2000, SBIA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1952))

Abstract

The ability to solve conflicting beliefs is crucial for multi- agent systems where the information is dynamic, incomplete and dis- tributed over a group of autonomous agents. The proposed distributed belief revision approach consists of a distributed truth maintenance sy- stem and a set of autonomous belief revision methodologies. The agents have partial views and, frequently, hold disparate beliefs which are au- tomatically detected by system’s reason maintenance mechanism. The nature of these conflicts is dynamic and requires adequate methodolo- gies for conflict resolution. The two types of conflicting beliefs addressed in this paper are Context Dependent and Context Independent Conflicts which result, in the first case, from the assignment, by different agents, of opposite belief statuses to the same belief, and, in the latter case, from holding contradictory distinct beliefs.

The belief revision methodology for solving Context Independent Con- flicts is, basically, a selection process based on the assessment of the cre- dibility of the opposing belief statuses. The belief revision methodology for solving Context Dependent Conflicts is, essentially, a search process for a consensual alternative based on a “next best” relaxation strategy.

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References

  1. de Kleer, J. 1986. An Assumption-Based Truth Maintenance System. Artificial Intelligence 28(2):127–224.

    Article  Google Scholar 

  2. Dragoni, A. F. Giorgini, P. and Puliti, P. 1994. Distributed Belief Revision versus Distributed Truth Maintenance. In Proceedings of the Sixth IEEE Conference on Tools with Artificial Intelligence, IEEE Computer Press.

    Google Scholar 

  3. Dragoni, A. F. and Giorgini, P. 1997. Belief Revision through the Belief Function Formalism in a Multi-Agent Environment. Third InternationalWorkshop on Agent Theories, Architectures and Languages, LNAI N. 1193, Springer-Verlag, 1997.

    Google Scholar 

  4. Cohen, P. R. 1985. Heuristic Reasoning about Uncertainty: an Artificial Intelligence Approach. Pitman, Boston, 1985.

    Google Scholar 

  5. Galliers, R. 1992. Autonomous belief revision and communication, Gärdenfors, P. ed. Belief Revision. Cambridge Tracts in Theoretical Computer Science, Cambridge University Press, N. 29.

    Google Scholar 

  6. Gaspar, G. 1991. Communication and Belief Changes in a Society of Agents: To-wards a Formal Model of an Autonomous Agent, Demazeau, Y. and Müller, J. P. eds. Decentralized A. I., Vol. 2, North-Holland Elsevier Science Publishers.

    Google Scholar 

  7. Jennings, N. R., Parsons, S., Noriega, P. and Sierra, C. 1998. On Argumentation-Based Negotiation. In Proceedings of the International Workshop on Multi-Agent Systems, Boston, USA.

    Google Scholar 

  8. Malheiro, B. and Oliveira, E. 1996. Consistency and Context Management in a Multi-Agent Belief Revision Tesbed. Wooldridge, M., Müller, J. P. and Tambe, M. eds. Agent Theories, Architectures and Languages, Springer-Verlag, Lecture Notes in AI, Vol. 1037.

    Google Scholar 

  9. Malheiro, B., Oliveira, E. 1997. Environmental Decision Support: a Multi-Agent Approach, The First International Conference on Autonomous Agents (Agents’97), Marina del Rey, California, USA.

    Google Scholar 

  10. Oliveira, E., Mouta, F. and Rocha, A. P. 1993. Negotiation and Conflict Resolution within a Community of Cooperative Agents. In Proceedings of the International Symposium on autonomous Decentralized Systems, Kawasaki, Japan.

    Google Scholar 

  11. Parsons, S., Sierra, C. and Jennings, N. R. 1998. Agents that reason and negotiate by arguing, Journal of Logic and computation, 8(3):261–292.

    Article  MathSciNet  Google Scholar 

  12. Sycara, K. 1990. Persuasive Argumentation in negotiation, Theory and Decision. 28:203–242.

    Google Scholar 

  13. Vreeswijk, A. W. 1997. Abstract argumentation systems. Artificial Intelligence 90(1–2).

    Google Scholar 

  14. Wittig, T. ed. 1992. ARCHON: An Architecture for Multi-Agent Systems, Ellis Horwood.

    Google Scholar 

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Malheiro, B., Oliveira, E. (2000). Solving Conflicting Beliefs with a Distributed Belief Revision Approach. In: Monard, M.C., Sichman, J.S. (eds) Advances in Artificial Intelligence. IBERAMIA SBIA 2000 2000. Lecture Notes in Computer Science(), vol 1952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44399-1_16

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  • DOI: https://doi.org/10.1007/3-540-44399-1_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41276-2

  • Online ISBN: 978-3-540-44399-5

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