Unit-I

Concepts in AI, Problem-solving in AI, Defining an AI problem as state space search, Production systems. AI problem characteristics.Heuristic Search Techniques : Generate-and-test, Hill climbing, Best first search, Problem-reduction, Constraint satisfaction.

Unit-II

Knowledge Representation in AI, Approaches and issues in knowledge representation . Knowledge representation using predicate logic, Resolution rules, Forward and backward reasoning, Semantic nets, Frames, Scripts and conceptual Dependency.

Unit-III

Expert systems : Architecture, the knowledge base, inference engine. Knowledge Acquisition, expert system development process as an example MYCIN , Natural language processing : Syntactic processing, Semantic analysis, Discourse and pragmatic processing.

Unit-IV

Introduction to pattern recognition : Recognition and classification process, Learning classification patterns, Visual image understanding, Image transformation, Preliminary concepts of parallel and distributed AI. Artificial neural network, LMS learning rule back propagation generalized Delta rule.

Unit-V

Prolog programming: Basic prolog concepts, Facts, Rules, Structures, Lists, Execution and meaning of prolog programs, Recursive programming, Backtracking with cuts.

Books

Artificial Intelligence, E.Rich and Knight. (2nd edition) TMH.
Introduction to AI and Expert Systems, D.W.Patterson (PHI)
Artificial Intelligence,P.H.Winston, Addison Wesley.
Principles of AI and Expert systems development ,D.W.Rolston, McGraw Hill.
Prolog programming, Cloksin and Melish, Galogtia pub.
Prolog through examples, I.Kononenko and N.Lavac, Galogtia