Course Title: 
Computational Intelligence
Course Code: 
Year Taught: 
Postgraduate (PG)
School of Arts and Sciences
School of Engineering

'Computational Intelligence' is a course offered in M. C. A. (Master of Computer Applications) program at Amrita Vishwa Vidyapeetham.

Artificial Intelligence – a Brief Review – Pitfalls of Traditional AI – Need for Computational Intelligence – Importance of Tolerance of Imprecision and Uncertainty – Constituent Techniques – Overview of Artificial Neural Networks - Fuzzy Logic – Evolutionary Computation.

Neural Network: Biological and Artificial Neuron, Neural Networks, Supervised and Unsupervised Learning. Single Layer Perceptron - Multilayer Perceptron – Backpropagation Learning.

Neural Networks as Associative Memories - Hopfield Networks, Bidirectional Associative Memory. Topologically Organized Neural Networks – Competitive Learning, Kohonen Maps.

Fuzzy Logic: Fuzzy Sets – Properties – Membership Functions - Fuzzy Operations. Fuzzy Logic and Fuzzy Inference - Applications. Evolutionary Computation – Constituent Algorithms. Swarm Intelligence Algorithms - Overview of other Bio-inspired Algorithms - Hybrid Approaches (Neural Networks, Fuzzy Logic, Genetic Algorithms etc.).

  • LaureneFausett, Fundamentals of Neural Networks, 2ndedition,Pearson, 1993
  • Ross T J, “Fuzzy Logic with Engineering Applications”, McGraw Hill, 1997.
  • Eiben A E and Smith J E, “Introduction to Evolutionary Computing”, Second Edition, Springer, Natural Computing Series, 2007.
  • Kumar S, “Neural Networks - A Classroom Approach”, Tata McGraw Hill, 2004.
  • Engelbrecht, A.P, “Fundamentals of Computational Swarm Intelligence”, John Wiley & Sons, 2006.
  • Konar. A, “Computational Intelligence: Principles, Techniques and Applications”, Springer Verlag, 2005.