Towards Explicit Integration of Knowledge in Expert Systems: An Analysis of MYClN’s Therapy Selection Algorithm

Jack Mostow, William Swartout

The knowledge integration problem arises in rule-based expert systems when two or more recommendations made by right-hand sides of rules must be combined. Current expert systems address this problem either by engineering the rule set to avoid it, or by using a single integration technique built into the interpreter, e.g., certainty factor combination. We argue that multiple techniques are needed and that their use -- and underlying assumptions -- should be made explicit. We identify some of the techniques used in MYCIN’s therapy selection algorithm to integrate the diverse goals it attempts to satisfy, and suggest how knowledge of such techniques could be used to support construction, explanation, and maintenance of expert systems.


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