Contents

• Unit 1. Introduction: Objective, scope and outcome of the course.

   

  Unit 2. Introduction to AI and Intelligent Agent: Different Approach of AI, Problem Solving : Solving Problems by Searching, Uninformed search, BFS, DFS, Iterative deepening, Bi directional search, Hill climbing, Informed search techniques: heuristic, Greedy search, A* search, AO* search, constraint satisfaction problems.

   

  Unit 3. Game Playing: Minimax, alpha-beta pruning, jug problem, chess problem, tiles problem

   

  Unit 4. Knowledge and Reasoning: Building a Knowledge Base: Propositional logic, first order logic, situation calculus. Theorem Proving in First Order Logic. Planning, partial order planning. Uncertain Knowledge and Reasoning, Probabilities, Bayesian Networks.

   

  Unit 5. Learning: Overview of different forms of learning, Supervised base learning: Learning Decision Trees, SVM, Unsupervised based learning, Market Basket Analysis, Neural Networks.

   

  Unit 6. Introduction to Natural Language Processing: Different issue involved in NLP, Expert System, Robotics.