Abstract

In this paper we show how to represent a set of logic propositions as an integer linear program and how to use its solution to determine the truth value of all the proposition given only a subset of their truth values. Thus a rule–based expert system might use this approach as inference engine. When we model an expert system knowledge base as an integer linear program, we can ask for what is a minimum set of premises needed in order to have an specific conclusion as true. Furthermore we can ask for what propositions become true once a subset of propositions are known to be true. Once the integer restriction is dismissed, we can ask for what conditions are necessary in order that a conclusion holds with certain probability. Thus we can have both a deterministic and stochastic model using practically the same paradigm.

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