1. CS621 : Artificial Intelligence Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 1 - Introduction

2. Resources Main Text: Artificial Intelligence: A Modern Approach by Russell & Norvik, Pearson, 2003. Other References: Principles of AI - Nilsson AI - Rich & Knight Knowledge Based Systems – Mark Stefik Journals AI, AI Magazine, IEEE Expert, Area Specific Journals e.g, Computational Linguistics Conferences IJCAI, AAAI

3. Areas of AI and Some Dependencies Search Vision Planning Machine Learning Knowledge Representation Logic Expert Systems RoboticsNLP

4. Allied Disciplines PhilosophyKnowledge Rep., Logic, Foundation of AI (is AI possible?) MathsSearch, Analysis of search algos, logic EconomicsExpert Systems, Decision Theory, Principles of Rational Behavior PsychologyBehavioristic insights into AI programs Brain ScienceLearning, Neural Nets PhysicsLearning, Information Theory & AI, Entropy, Robotics Computer Sc. & Engg.Systems for AI

5. Difference between UG-AI course and PG-AI course Search DFS, BFS, A* (UG) Iterative Deepening, α-β pruning, Island search, probabilistic methods (PG) Logic Propositional Calculus, Predicate Calculus (UG) Belief world, non-monotonic logic, probabilistic reasoning (PG) Knowledge Representation Predicate calculus, Semantic Net, Frame (UG) Script, Conceptual Dependency, Uncertainty (PG)

6. Other Material to be Covered Classical Machine Learning Learning from examples Decision Trees Analogical Learning Explanation Based Learning Computer Vision AI methods in Computer Vision Planning Rule Based Stochastic

7. Suggested Seminar Areas Distributed AI (Blackboard Architecture) Robotics Algorithms Semantic Web (Description Logic, RDF, OWL) Prediction, Forecasting Brain Science and AI Computer Games