Skip to main content

How to Choose the Optimal Policy in Multi-agent Belief Revision?

  • Conference paper
  • First Online:
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

  • 707 Accesses

Abstract

In multi-agent system, it is not enough to maintain the coherence of single agent’s belief set only. By communication, one agent removing or adding a belief sentence may influence the certainty of other agents’ belief sets. In this paper, we investigate carefully some features of belief revision process in different multi-agent systems and bring forward a uniform framework — Bereframe. In Bereframe, we think there are other objects rather than maintaining the coherence or maximize certainty of single belief revision process, and agent must choose the optimal revision policy to realize these. The credibility measure is brought forward, which is used to compute the max credibility degree of the knowledge background. In cooperative multi-agent system, agents always choose the combinative policy to maximize the certainty of whole system’s belief set according to the welfare principle. And in semi-competitive multi-agent system, agents choose the revision policy according to the Pareto efficiency principle. In competitive multi-agent system, the Nash equilibrium criterion is applied into agent’s belief revision process.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alchouurron, C., Gardenfors, P., Makinson, D.: On the logic of theory change: Partial meet contraction functions and their associated revision functions. Journal of Symbolic Logic 50 (1985) 510–530

    Article  MathSciNet  Google Scholar 

  2. Gardenfors, P.: The dynamics of belief systems: Foundations vs. coherence theories. Revue Internationale de Philosophie 171 (1990) 24–46

    Google Scholar 

  3. Shafer, G.: A mathematical theory of evidence. Princeton, NJ: Princeton University Press (1976)

    MATH  Google Scholar 

  4. Liu W., Williams M.A.: A framework for multi-agent belief revision (Part I: The role of ontology). In: Foo N. (ed.) 12th Australian Joint Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence. Sydney. Australia: Springer-Verlag (1999) 168–179

    Google Scholar 

  5. Liu W., Williams M.A.: A framework for multi-agent belief revision. Studia Logica 67 (2001) 219–312

    Article  MathSciNet  Google Scholar 

  6. Benedita Malheiro, N.R. Jennings, Eugenio Oliveira.: Belief revision in Multi-agent Systems. In: Proceedings 11th European Conf. on Artificial Intelligence (ECAI-94) (1993) 294–298

    Google Scholar 

  7. A.F. Dragoni, Paolo Giorgini, Marco Baffetti.: Distributed Belief Revision vs. Belief Revision in a Multi-Agent environment: first results of a simulation experiment In: Magnus Boman and Walter Van de Velde (Eds.), Multi-agent Rationality, LNCS No. 1237, Springer-Verlag (1997)

    Google Scholar 

  8. Noa E. Kfir-dahav, Moshe Tennenholtz.: Multi-agent belief revision. In: 6th Conference on Theoretical Aspects to Rationality and Knowledge (1996) 175–194

    Google Scholar 

  9. R. van der Meyden.: Mutual Belief Revision. In: Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning, Bonn (1994) 595–606

    Google Scholar 

  10. Nir Friedman, Joseph Y. Halpern.: Belief Revision: A Critique. In: Aiello, L.C., Doyle, J., Shapiro, S.C., (eds.) Principles of Knowledge Representation and Reasoning: Proceedings of the Fifth International Conference (KR’96), San Francisco, Morgan Kaufmann (1996) 421–431

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gao, Y., Sun, Z., Li, N. (2003). How to Choose the Optimal Policy in Multi-agent Belief Revision?. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_121

Download citation

  • DOI: https://doi.org/10.1007/3-540-39205-X_121

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics