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:-
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.
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.
Building an Expert System: Expert system development, Selection of the tool, Acquiring Knowledge, Building process.
Problems with Expert Systems: Difficulties, common pitfalls in planning, dealing with domain experts, difficulties during development.
- Elain Rich and Kevin Knight, “Artificial Intelligence”, Tata McGraw-Hill, New Delhi,
- Waterman D.A., “A Guide to Expert Systems”, Addison Wesley Longman,
- Stuart Russel and other Peter Norvig, “Artificial Intelligence – A Modern Approach”, Prentice-Hall,
- Patrick Henry Winston, “Artificial Intelligence”, Addison Wesley,
- Patterson, Artificial Intelligence & Expert System, Prentice Hall India,1999.
- Hayes-Roth, Lenat, and Waterman: Building Expert Systems, Addison Wesley,
- Weiss S.M. and Kulikowski C.A., “A Practical Guide to Designing Expert Systems”, Rowman &Allanheld, New Jersey,
Below is the link to download Expert Systems notes.