1. FT228/4 Knowledge Based Decision Support Systems Rule-Based Systems Ref: Artificial Intelligence A Guide to Intelligent Systems Michael Negnevitsky – Aungier St. Call No. 006.3

2. Knowledge Knowledge is a theoretical or practical understanding of a particular doamin Knowledge is the sum of what is currently know Those who possess knowledge are termed experts

3. Knowledge What is an expert ? Deep knowledge Strong practical experience How do you represent how experts think?

4. Knowledge Representation Programming language is a means of representing knowledge Procedural knowledge “how to” Knowledge about how to perform some task Declarative knowledge “what is “

5. Knowledge Representation Production Rules IT-THEN expressions IF some condition(s) exists THEN perform some action(s) Test-Action rules Rule-Based System = Intelligent Production System

6. Knowledge Representation Rule Part 1 Antecedent (premise or condition) IF part Test part Rule Part 2 Consequent (conclusion or action) THEN part Action part IF THEN A rule fires when its condition part is satisified and its action part is executed

7. Knowledge Representation Rule can have multiple antecedents Conjunction AND Disjunction OR Or a combination of both Consequent can have multiple clauses IF THEN

8. Knowledge Representation Antecedent consists of An object (linguistic object) Its value Linked by an operator Identifies the object and assigns the value E.g is, are, is not, are not Mathematical operators e.g =, >, < Consequent consists of An object A value Connected by an operator

9. Knowledge Representation Rules represent Relations Recommendations Directives Strategies Heuristics

10. Production System Model Long Term Memory Production Rule Short Term Memory Fact Reasoning Conclusion

11. Rule-Based System for Tic-Tac- Toe What rules do we need ? Rules may have tests that are satisfied at the same time – need some mechanism for selecting right rule