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Modeling knowledge dynamics in multi-agent systems based on informants

Published online by Cambridge University Press:  22 February 2012

Luciano H. Tamargo*
Affiliation:
Department of Computer Science and Engineering, Artificial Intelligence Research and Development Laboratory, Universidad Nacional del Sur, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
Alejandro J. García*
Affiliation:
Department of Computer Science and Engineering, Artificial Intelligence Research and Development Laboratory, Universidad Nacional del Sur, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
Marcelo A. Falappa*
Affiliation:
Department of Computer Science and Engineering, Artificial Intelligence Research and Development Laboratory, Universidad Nacional del Sur, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
Guillermo R. Simari*
Affiliation:
Department of Computer Science and Engineering, Artificial Intelligence Research and Development Laboratory, Universidad Nacional del Sur, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina

Abstract

In this paper, we model knowledge dynamics in agents’ belief bases in a collaborative multi-agent system (MAS). Four change operators are introduced: expansion, contraction, prioritized revision, and non-prioritized revision. For all of them, both constructive definitions and an axiomatic characterization by representation theorems are given. We formally justify minimal change, consistency maintenance, and non-prioritization principles. These operators are based on an epistemic model for multi-source belief revision in which a rational way to weigh the beliefs using a credibility order among agents is developed. The defined operators can be seen as skills added to the agents improving the collective reasoning of a MAS.

Type
Articles
Copyright
Copyright © Cambridge University Press 2012

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