EI7201 Artificial Intelligence & Expert Systems Syllabus
RGTU/RGPV Artificial Intelligence & Expert Systems Syllabus
Electronics and Instrumentation EI VII-7th Semester Syllabus
EI7201 Artificial Intelligence & Expert Systems Course Contents:
Unit-I
Basic Problem solving methods: Production systems-state space search, control strategies, Heuristic search, forward and backward reasoning, Hill climbing techniques, Breadth first search, Depth first search, Best search, staged search.
Basic Problem solving methods: Production systems-state space search, control strategies, Heuristic search, forward and backward reasoning, Hill climbing techniques, Breadth first search, Depth first search, Best search, staged search.
Unit-II
Knowledge Representation: Predicate logic, Resolution question Answering, Nonmonotonic Reasoning, statistical and probabilistic reasoning, Semantic Nets, Conceptual Dependency, frames and scripts.
Unit-III
AI languages: Important characteristics of AI languages - PROLOG, LISP.
Unit -IV
Introduction to Expert Systems: Structure of an Expert system interaction with an expert, Design of an
Expert system.
Unit-V
Fundamentals of Artificial Neural Network (ANN), perceptrons, Back propagation, Cohenon self organizing network, Hop field networks
References:
- Rich E and Knight K, Artificial Intelligence, TMH New Delhi.
- Nelsson N.J., Principles of Artificial Intelligence, Springer Verlag, Berlin.
- Barr A, Fergenbaub E.A. and Cohen PR. Artificial Intelligence, Addison Wesley, Reading
- Waterman D.A., A guide to Expertsystem, Adision - Wesley, Reading
- Artificial Intelligence Hand book, Vol. 1-2, ISA, Research Triangle Park.
- Kos Ko B, Neural Networks and Fuzzy system –PHI.
- Haykin S, Artificial Neural Networks-Comprehensive Foundation, Asea, Pearson.
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