Expert Systems: Principles and ProgrammingIntroduction to Expert Systems 2 The Representation of Knowledge 3 Methods of Inference 4 Reasoning Under Uncertainty 5 Inexact Reasoning 6 Design of Expert Systems 7 Introduction to CLIPS 8 Advanced Pattern Matching 9 Modular Design, Execution Control, and Rule Efficiency 10 Procedural Programming 11 Classes, Instances, and Message-Handlers 12 Expert System Design Examples Appendices A: Some Useful Equivalences B: Some Elementary Quantifiers and The ir Meanings C: Some Set Properties D: CLIPS Support Information E: CLIPS Commands and Functions Summary F: CLIPS BNF G: Software Resources. |
Contents
INTRODUCTION TO EXPERT SYSTEMS | 1 |
THE REPRESENTATION OF KNOWLEDGE | 63 |
METHODS OF INFERENCE | 107 |
Copyright | |
22 other sections not shown
Common terms and phrases
actions activated addition algorithm allow answer application argument assert attribute backward chaining belief block called certainty Chapter CLIPS combination command conclusion conditional consider contains correct crlf cycle decision deffacts defined defrule described designed determine device discussed elements engine equal error evidence example execution expert system expression fact factors field Figure fire frame function fuzzy set given goal human hypothesis important indicate inference input knowledge language logic matches means method move node Notice object operator output pattern person phase possible predicate printout probability problem procedure production question reasoning relation removed represent retract rule salience satisfied sensor shown shows simple single solve specific statement string structure symbol Table theory tree true uncertainty valid variable write written X X X