Skip to main content

Measuring agreement and harmony in multi-agent societies: A first approach

  • Conference paper
  • First Online:
  • 134 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 991))

Abstract

The existence of independent goals is a natural and often desirable characteristic in societies of autonomous agents. Depending on the application, some societies might be more tolerant to independence than others. Nevertheless, agents must have means for negotiate their goals gracefully and efficiently. Indeed, we find in the literature some proposals of goal negotiation Strategies. At the present state of the art, there is a need for frameworks under which one can compare such strategies and study their influence in the social behavior of the agents. We present here some analytical tools to measure the negotiation characteristics in a society. The underlying notions in these tools are the ideas of agreeability and harmony. By agreeability we mean the ability of an agent to adopt the goals of another agent and/or induce their own goals on another agent. Harmony is the global agreeability in a society. We give mathematical definitions for these notions and illustrate how the definitions can be applied to the study of societies at various levels.

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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. LAVRAC, N. Inductive Concept Learning Using Background Knowledge. In: Pequeno, T.; Carvalho, F. (eds.) Proceedings of the XI Brazilian Symposium on Artificial Intelligence. Fortaleza, Universidade Federal do Ceará, 1994. p. 1–16.

    Google Scholar 

  2. BOND, A.H.; GASSER, L. (eds.) Readings in Distributed Artificial Intelligence. San Mateo, California: Morgan Kaufmann, 1988.

    Google Scholar 

  3. DECKER, K.S. Distributed Problem-Solving Techniques: a Survey. IEEE Transactions on Systems, Man and Cybernetics, 17(5):729–740, September/October 1987.

    Google Scholar 

  4. DEMAZEAU, Y.; MULLER, J.P. (eds.) Decentralized Artificial Intelligence. Morgan Kaufmann, 1990.

    Google Scholar 

  5. FAGIN, R.; HALPERN, J.Y.; YARDI, M.V. A Model-Theoretic Analysis of Knowledge. Journal of the ACM, 2:382–428, April 1991.

    Article  Google Scholar 

  6. GALLIER, J.R. The Positive Role of Conflict in Cooperative Multi-Agent Systems. In: DEMAZEAU, Y.; MULLER, J.P. (eds.) Decentralized Artificial Intelligence. Morgan Kaufmann, 1990.

    Google Scholar 

  7. KHEDRO, T.; GENESERETH, M.R. Modeling Multiagent Cooperation as Distributed Constraint Satisfaction Problem Solving. In: Cohn, A. (ed.) Proceedings of the 11th European Conference on Artificial Intelligence. New York, J. Wiley & Sons, 1994. p. 249–253.

    Google Scholar 

  8. LIPSCHUTZ, S. General Topology. McGraw-Hill, 1965.

    Google Scholar 

  9. LLOYD, J.W. Foundations of Logic Programming. Berlin, Springer-Verlag, 1984.

    Google Scholar 

  10. OLIVEIRA, F.M.; VICCARI, R.M.; COELHO, H. A Topological Approach to Equilibration of Concepts. In: Pequeno, T.; Carvalho, F. (eds.) Proceedings of the XI Brazilian Symposium on Artificial Intelligence. Fortaleza, Universidade Federal do Ceará, 1994. p. 527–523.

    Google Scholar 

  11. SICHMAN, J.; DEMAZEAU,Y.; BOISSIER, O. When can Knowledgebased Systems be Called Agents? In: IX Simpósio Brasileiro De Inteligência Artificial, Rio de Janeiro, RJ, Out. 1992. Proceedings. Rio de Janeiro, SBC, 1992.

    Google Scholar 

  12. WAINER, J. Yet Another Semantics of Goal and Goal Priorities. In: Cohn, A. (ed.) Proceedings of the 11th European Conference on Artificial Intelligence. New York, J. Wiley & Sons, 1994. p. 269–273.

    Google Scholar 

  13. WERNER, E. Distributed Cooperation Algorithms. In: DEMAZEAU, Y.; MULLER, J.P. (eds.) Decentralized Artificial Intelligence. Morgan Kaufmann, 1990.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Jacques Wainer Ariadne Carvalho

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

de Oliveira, F.M. (1995). Measuring agreement and harmony in multi-agent societies: A first approach. In: Wainer, J., Carvalho, A. (eds) Advances in Artificial Intelligence. SBIA 1995. Lecture Notes in Computer Science, vol 991. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0034816

Download citation

  • DOI: https://doi.org/10.1007/BFb0034816

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60436-5

  • Online ISBN: 978-3-540-47467-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics