Expert Systems

is a branch in Artificial Intelligence that deals with a computer system that has decision-making ability just like human experts.

Below is the syllabus for
Expert Systems:-

Unit-I

Introduction to AI programming languages, Blind search strategies, Breadth-first – Depth-first – Heuristic search techniques Hill Climbing – Best first – A Algorithms AO* algorithm – game tress, Min-max algorithms, game playing – Alpha-beta pruning.

Knowledge representation issues predicate logic – logic programming Semantic nets- frames and inheritance, constraint propagation; Representing Knowledge using rules, Rules-based deduction systems.

Unit-II

Introduction to Expert Systems, Architecture of expert system, Representation and organization of knowledge, Basics characteristics, and types of problems handled by expert systems.

Expert System Tools:
Techniques of knowledge representations in expert systems, knowledge engineering, system-building aids, support facilities, stages in the development of expert systems.

Unit-III

Building an   Expert   System:
Expert system development, Selection of the tool, Acquiring Knowledge, Building process.

Unit-IV

Problems with Expert Systems:
Difficulties, common pitfalls in planning, dealing with domain experts, difficulties during development.

Text Books

  1. Elain Rich and Kevin Knight, “Artificial Intelligence”, Tata McGraw-Hill, New Delhi,
  2. Waterman D.A., “A Guide to Expert Systems”, Addison Wesley Longman,

Reference Books

  1. Stuart Russel and other Peter Norvig, “Artificial Intelligence – A Modern Approach”, Prentice-Hall,
  2. Patrick Henry Winston, “Artificial Intelligence”, Addison Wesley,
  3. Patterson, Artificial Intelligence & Expert System, Prentice Hall India,1999.
  4. Hayes-Roth, Lenat, and Waterman: Building Expert Systems, Addison Wesley,
  5. Weiss S.M. and Kulikowski C.A., “A Practical Guide to Designing Expert Systems”, Rowman &Allanheld, New Jersey,

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Expert Systems

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