EI7201 Artificial Intelligence & Expert Systems EI 7th (Fifth) sem Electronics and Instrumentation(EI) Syllabus

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.

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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