Introduction: AI Problems – AI techniques – Criteria for success. Problems,Problem Spaces, Search: State space search – Production Systems – ProblemCharacteristics – Issues in design of Search.

Heuristic Search techniques: Generate and Test – Hill Climbing –Best-Fist, Problem Reduction, Constraint Satisfaction, Means-end analysis.

Knowledge representation issues: Representations and mappings –Approaches to Knowledge representations – Issues in Knowledge representations –Frame Problem.

Using Predicate Logic: Representing simple facts in logic – Representing Instance and Isa relationships – Computable functions and predicates –Resolution – Natural deduction.

Representing knowledge using rules: Procedural Vs Declarative knowledge – Logic programming – Forward Vs Backward reasoning – Matching-Control knowledge Brief explanation of Expert Systems-Definition- Characteristics-architecture-Knowledge Engineering- Expert System Life Cycle-Knowledge Acquisition Strategies-Expert System Tools.