ICC   25427
INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Unidad Ejecutora - UE
artículos
Título:
Merging Existential Rules Programs in Multi-Agent Contexts through Credibility Accrual
Autor/es:
MARIA VANINA MARTINEZ; CRISTHIAN ARIEL DAVID DEAGUSTINI; FALAPPA, MARCELO A.; JUAN CARLOS L. TEZE; GUILLERMO R. SIMARI
Revista:
INFORMATION SCIENCES
Editorial:
ELSEVIER SCIENCE INC
Referencias:
Lugar: Amsterdam; Año: 2020 vol. 555 p. 236 - 259
ISSN:
0020-0255
Resumen:
Merging operators represent a significant tool to extract a consistent and informative view from a set of agents. The consideration of practical scenarios where someagents can be more credible than others has contributed to substantially increase the interest in developing systems working with trust models. In this context, we propose an approach to the problem of merging knowledge in a multiagent scenario where every agent assigns to other agents a value reflecting its perception on how credible each agent is. The focus of this paper is the introduction of an operator for merging Datalog± ontologies considering agents? credibility. We present a procedure to enhance a conflict resolution strategy by exploiting the credibility attached to a set of formulas; the approach is based on accrual functions that calculate the value of formulas according to the credibility of the agents that inform them. We show how our new operator can obtain the best-valued knowledge base among consistent bases available, according to the credibilities attached to the sources.