Course Objectives:

  1. To understand the basic concepts of AI and problem solving
  2. To analyze and formalize the problem as a state space, graph, design heuristics and select amongst different search techniques to solve them
  3. To represent knowledge and draw inferences
  4. To explore learning techniques and existing expert systems

Unit I

Introduction: The AI problems; what is an AI technique; Characteristics of AI applications Problem Solving, Search and Control Strategies General Problem solving; Production systems; Control strategies: forward and backward chaining Exhaustive searches: Depth first Breadth first search.

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Unit II

Heuristic Search Techniques: Hill climbing; Branch and Bound technique; Best first search and A* algorithm; AND/OR Graphs; Problem reduction and AO* algorithm; Constraint Satisfaction problems Game Playing Minmax search procedure; Alpha-Beta cutoffs; Additional Refinements

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Unit III

Knowledge Representation & Reasoning:- Propositional logic, First order predicate logic, Inferencein FOPL, Skolemnisation; Resolution Principle and Unification; Forward & Backward chaining, Inference Mechanisms Horn’s Clauses; Semantic Networks; Frame Systems and Value Inheritance; Conceptual Dependency

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Unit IV

Learning Techniques: – Supervised and unsupervised learning, Decision trees, Statistical learning models, Reinforcement learning.

Expert Systems: Introduction to Expert Systems, Architecture of Expert Systems; Expert System Shells; Knowledge Acquisition; Case Studies: MYCIN, Learning, Rote Learning; Learning by Induction; Explanation based learning.

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  1. Elaine Rich and Kevin Knight: Artificial Intelligence- Tata McGraw Hill.
  2. Dan W.Patterson, Introduction to Artificial Intelligence and Expert Systems- Prentice Hall of India.
  3. Nils J.Nilsson: Principles of Artificial Intelligence- Narosa Publishing house.
  4. Artificial Intelligence : A Modern Approach, Stuart Rusell, Peter Norvig, Pearson Education
  5. Artificial Intelligence, Winston, Patrick, Henry, Pearson Education

Course Outcomes:  After successful completion of the course students will learn the following:-

  1. Analyze and formalize problem and solve them using AI techniques
  2. Use Heuristic search techniques for game playing and other problems
  3. Represent diverse knowledge using AI and analyze
  4. Understand and design an expert system
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