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Evidential support logic, FRIL and case based reasoning
Author(s) -
Baldwin J. F.
Publication year - 1993
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550080904
Subject(s) - computer science , rule of inference , model based reasoning , inference , case based reasoning , artificial intelligence , reasoning system , knowledge representation and reasoning , opportunistic reasoning , expert system , deductive reasoning , representation (politics) , knowledge base , non monotonic logic , complete information , data mining , mathematics , mathematical economics , political science , law , politics
Knowledge representation for expert systems and decision support systems is often in the form of rules and answering queries is performed by backward and forward reasoning. Case based reasoning is an alternative to this. In its most basic form, a query is answered by reference with data given as part of the query to similar cases in a data base. In this article we will use a mixture of case based reasoning and rule inference methods. Rules will represent generalizations of information relevant to prototypical cases. the prototypical cases are chosen from a database of examples. Partial matchings of features in a rule are used to infer a conclusion even when information to evaluate the body of the rule is incomplete. Features are given importance weights and inferred conclusions from various rules are combined using mass assignment theory © 1993 John Wiley & Sons, Inc.