著者

鈴木 義崇 東条 敏

出版者

人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.19, no.1, pp.57-67, 2004

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Belief fusion, instead of AGM belief revision, was first proposed to solve the problem of inconsistency, that arised from repetitive application of the operation when agents' knowledge were amalgamated. In the preceding work of Maynard-Reid II and Shoham, the fusion operator is applied to belief states, which is total preorders over possible worlds which is based on the semantics of belief revision. Moreover, they introduced the pedigreed belief state, which represented multiple sources of belief states, ordered by a credibility ranking. However in the theory, all the sources must be totally ordered and thus applicable area is quite restrictive. In this paper, we realize the fusion operator of multiple agents for partially ordered sources. When we consider such a partial ranking over sources, there is no need to restrict that each agent has total preorders over possible worlds. The preferential model, based on the semantics on nonmonotonic reasoning, allows each agent to have strict partial orders over possible worlds. Especially, such an order is called a preferential relation, that prescribes a world is more plausible than the other. Therefore, we introduce an operation which combines multiple preferential relations of agents. In addition, we show that our operation can properly include the ordinary belief fusion.