Author: Lozinskii Eliezer L.
Publisher: Taylor & Francis Ltd
ISSN: 1362-3079
Source: Journal of Experimental & Theoretical Artificial Intelligence, Vol.12, Iss.1, 2000-01, pp. : 69-89
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Abstract
Given a system description and its observed behaviour, there usually exist several possible explanations of the situation. Different explanations may contradict one another and suggest conflicting actions. So, in order to take proper actions sanctioned by the real situation, we need to single out an explanation that is most adequate to the reality. Existing methods for determining of such a best explanation require an extensive statistical knowledge about the system behaviour, which often is either only partially available or not satisfactorily reliable. Trying to overcome this lack of data, we introduce the notion of evidence as a measure of credibility of beliefs based on the semantic information contained in the system and supplied by the observations. Reasoning by evidence is applied to the process of determining a best abductive explanation. The notion of conjecture is presented as a generalization of explanation.Then reasoning by evidence is applied to testing and refining of diagnoses.
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