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.
Reference Book:
R1. Stuart Russell and Peter Norvig, “Artificial Intelligence a modern Approach “, 3 rd Edition Perason Education., 2009 R2. George F Luger , “Artificial Intelligence “,5 th Edition , Pearsons Education Publ, 2012. R2. V S JANAKI RAMAN, K.SARUKESI, P.GOPALAKRISHNAN, “Foundations of Artificial Intelligent and Expert Systems”, MacMillan India limited.,
Text Book:
T1. Elaine rich and Kelvin Knight, “Artificial Intelligence “, Tata McGrawhill Publication,3 rd Edition, 2010.(chapters 1- 6 ).