Argumentation as distributed belief revision: conflict resolution in decentralized co-operative multi-agent systems

• Type: Article in International Conference Proceedings Book
• Date: 2001

Authors

Benedita Malheiro (Author) Other; Eugénio Oliveira (Author) FEUP

Conference proceedings International

Title: Progress in Artificial Intelligence: Knowledge Extraction, Multi-agent Systems, Logic Programming, and Constraint Solving

10th Portuguese Conference on Artificial Intelligence, EPIA 2001

Porto, Portugal, December 17-20, 2001

Indexing

Scopus

Scientific classification

FOS: Engineering and technology > Other engineering and technologies

CORDIS: Physical sciences > Computer science > Cybernetics > Artificial intelligence

Other information

Abstract (EN): Decentralised co-operative multi-agent systems are computational systems where conflicts are frequent due to the nature of the represented knowledge. Negotiation methodologies, in this case argumentation based negotiation methodologies, were developed and applied to solve unforeseeable and, therefore, unavoidable conflicts. The supporting computational model is a distributed belief revision system where argumentation plays the decisive role of revision. The distributed belief revision system detects, isolates and solves, whenever possible, the identified conflicts. The detection and isolation of the conflicts is automatically performed by the distributed consistency mechanism and the resolution of the conflict, or belief revision, is achieved via argumentation. We propose and describe two argumentation protocols intended to solve different types of identified information conflicts: context dependent and context independent conflicts. While the protocol for context dependent conflicts generates new consensual alternatives, the latter chooses to adopt the soundest, strongest argument presented. The paper shows the suitability of using argumentation as a distributed decentralised belief revision protocol to solve unavoidable conflicts.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12