A framework for assigning probabilities in knowledge-based systems
This paper discusses a framework for assigning probabilities to rules in an expert system to deal with uncertainty knowledge processing. The objective is to enable a system to respond to environmental or uncontrollable factors in a strategic manner. We define guards for representing probabilities and then discuss operators and axioms, as part of a problem solver, for guiding probability assignments. We then demonstrate the capabilities of this problem solver by applying to an example taken from game theory.
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