Outline:
1. Problem formulation, Problem Definition – Production systems, Control strategies, Search strategies. Problem characteristics, Production system characteristics – Specialized production systems.
2. Problem solving methods – Problem graphs, Matching, Indexing and Heuristic functions – Measure of performance and analysis of search algorithms - Game playing.
3. Knowledge representation, Knowledge representation using Predicate logic, Introduction to predicate calculus, Resolution, Use of predicate calculus, Knowledge representation using other logic.
4. Structured representation of knowledge - Basic plan generation systems – Strips – Advanced plan generation systems – K strips – D Comp. Expert systems – Architecture - Roles – Knowledge Acquisition – Meta knowledge, Heuristics - Knowledge representation – Production based system, Frame based system.
5. Inference – Backward chaining, Forward chaining, Rule value approach, Fuzzy reasoning – Certainty factors, Bayesian probability - Strategic explanations – Why, Why not and how explanations. Learning – Machine learning, adaptive learning - Typical expert systems.
Books:
1. Elaine Rich, "Artificial Intelligence", 1985, McGraw Hill.
2. Nilsson N.J., "Principles of Artificial Intelligence", 1992, Narosa.
