Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/5127
Título: Improving Assumption based Distributed Belief Revision
Autor: Malheiro, Benedita
Oliveira, Eugénio
Palavras-chave: Multiagent Systems/Sistemas Multiagente
Distributed Coherence Maintenance
Data: 1995
Editora: IOS Press
Citação: Benedita Malheiro; Eugénio Oliveira. Improving Assumption based Distributed Belief Revision, In Frontiers in Artificial Intelligence and Applications, Fifth Scandinavian Conference on Artificial Intelligence 1995, Trondheim, Norway, 29-31 May, 1995, 41-50, ISBN: 978 90 5199 221 2. Trondheim, Norway: IOS Press, 1995.
Relatório da Série N.º: SCAI;95
Frontiers in artificial intelligence and applications;Vol. 28
Resumo: Belief revision is a critical issue in real world DAI applications. A Multi-Agent System not only has to cope with the intrinsic incompleteness and the constant change of the available knowledge (as in the case of its stand alone counterparts), but also has to deal with possible conflicts between the agents’ perspectives. Each semi-autonomous agent, designed as a combination of a problem solver – assumption based truth maintenance system (ATMS), was enriched with improved capabilities: a distributed context management facility allowing the user to dynamically focus on the more pertinent contexts, and a distributed belief revision algorithm with two levels of consistency. This work contributions include: (i) a concise representation of the shared external facts; (ii) a simple and innovative methodology to achieve distributed context management; and (iii) a reduced inter-agent data exchange format. The different levels of consistency adopted were based on the relevance of the data under consideration: higher relevance data (detected inconsistencies) was granted global consistency while less relevant data (system facts) was assigned local consistency. These abilities are fully supported by the ATMS standard functionalities.
URI: http://hdl.handle.net/10400.22/5127
ISBN: 978 90 5199 221 2
ISSN: 0922-6389
Versão do Editor: http://www.iospress.nl/book/scai-95/
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