AING354 Knowledge Representation and Reasoning

Contents for the Course

1- Introduction & Motivation: What is symbolic AI? Contrast with ML. Cultural examples of rule-based reasoning. 

2-Preliminaries & Syntax. Propositional logic recap, notation conventions, 

3- First-Order Logic (FOL) as a Language: Quantifiers, predicates, connectives. Emphasis on expressiveness and limitations. Expressing Knowledge in FOL. Translating natural language into FOL. Use of culturally relevant examples and rituals.

 4- Resolution & Inference in FOL: Unification, resolution rule, refutation. Visual walkthroughs of inference chains.

 5- Horn Clauses & Definite Clause Logic: Syntax, semantics, and procedural interpretation. Link to Prolog-style reasoning.

 6- Production Rules & Rule-Based Systems: Forward/backward chaining. Comparison with Horn clause logic. Use in expert systems.

 7: Procedural Control: control strategies, rule ordering, conflict resolution. 

 8- Vagueness, Uncertainty & Fuzzy Rules: Dempster-Shafer basics, fuzzy sets, fuzzy IF-THEN rules. Contrast with crisp logic.

9- More on implementation if time allows.

Text Book: Lecture Notes by M.Bodur, 80% copied from the original coursebible "Ronald J. Brachman and Hector J. Levesque, Knowledge representation and reasoning, Inc., ISBN: 1-55860-932-6, 2004 Elsevier

Other Books: N.Kasabov, Knowledge Engineering, 2nd ed. 1996 MIT Press.