Generalised alpha-beta pruning as a guide to expert system question selection
Proc. of the fifth technical conference of the British Computer Society Specialist Group on Expert Systems on Expert systems 85
Building expert systems
Artificial Intelligence
Communications of the ACM
Introduction to Expert Systems
Introduction to Expert Systems
Artificial Intelligence and the Design of Expert Systems
Artificial Intelligence and the Design of Expert Systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A cost-reducing question-selection algorithm for propositional knowledge-based systems
Annals of Mathematics and Artificial Intelligence
A cost-reducing question-selection algorithm for propositional knowledge-based systems
Annals of Mathematics and Artificial Intelligence
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When initial data are not sufficient to accomplish inference in a knowledge‐based system, more information may be needed. The task of inference guiding or question‐asking in that situation is to select missing information to confirm. We present an inference guiding method for propositional knowledge‐based systems. Our computational experiments show that the new method is significantly better than the methods currently used in many knowledge‐based systems.