Chapter 20 Expert System Chapter 20 Expert System Artificial Intelligence ดร. วิภาดา เวทย์ประสิทธิ์ ภาควิชาวิทยาการคอมพิวเตอร์ คณะ วิทยาศาสตร์ มหาวิทยาลัยสงขลานครินทร์
Artificial Intelligence Lecture 44Page 2 Expert System p. 547 MYCIN (1976) see section 8.2 –backward chaining + certainty factor and rule-based systems p.233 –Bayesian network p. 239 –Fuzzy logic p. 246 –Probability and Bayes’ theorem p. 231 PROSPECTOR (1976), DENDRAL (1978) expert systems shells EMYCIN
Artificial Intelligence Lecture 44Page 3 Expert System using domain knowledge knowledge representation p. 297 reasoning with the knowledge, explanation Knowledge acquisition (p. 553) 1) entering knowledge 2) maintaining knowledge base consistency 3) ensuring knowledge base completeness MOLE (1988) is a knowledge acquisition system for heuristic classification problems such as diagnosing diseases.
Artificial Intelligence Lecture 44Page 4 Expert System problem : then number of rules may be large control structure depend on the specific characteristic of the problrem 1) Brittleness : no general knowledge that can be used, the data is out of date 2) Lack of meta-knowledge : the limitation of the control operation for reasoning 3) Knowledge acquisition : difficult to transform the knowledge from human to machine 4) Validation : the correctness of the knowledge in the system, no formal proof that machine is better than human or human better than machine.