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Unit 1. Artificial Intelligence: Introduction to AI and knowledge based Expert systems: Introduction, Importance and definition of AI, ES, ES building tools and shells.
Unit 2. Knowledge Representation: Concept of knowledge, Representation of knowledge using logics rules, Frames. Procedural versus. Declarative knowledge, Forward versus backward chaining. Control Strategies: Concept of heuristic search, Search techniques depth first search, Breath first search, Generate & test hill climbing, Best first search.
Unit 3. Artificial Neural Network: Biological neurons and synapses, Characteristics artificial Nneural networks, Types of activation functions. Perceptions: Perception representation, Limitations of perceptrons. Single layer and multiplayer perceptrons. Perceptron learning algorithms.
Unit 4. Basic Concepts in Learning ANN: Supervised learning, Back propagation algorithm, Unsupervised learning, Kohonen’s hop field network & algorithm.
Unit 5. Fuzzy Logic: Fuzzy logic concepts, Fuzzy relation and membership functions, Defuzzufication, Fuzzy controllers. Genetic algorithm: Concepts, coding, Reproduction, Crossover, Mutation, Scaling and fitness.