Artificial Intelligence

Artificial Intelligence. Instructor: Prof. P. Dasgupta, Department of Computer Science and Engineering, IIT Kharagpur. This course provides an introduction to artificial intelligence, covering topics: Problem Solving by Search, Searching with Costs, Heuristic Search: A* and Beyond, Searching Game Trees, Knowledge Based Systems: Logic and Deduction, First Order Logic, Inference in First Order Logic, Logic Programming: Prolog, Prolog: Exercising Control, GraphPLAN and SATPlan, Reasoning with Bayes Networks. (from

Lecture 13 - Logic Programming: Prolog

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Lecture 01 - Introduction to Artificial Intelligence
Lecture 02 - Problem Solving by Search: State Space Search
Lecture 03 - Searching with Costs
Lecture 04 - Informed State Space Search: The Notion of Heuristics, Algorithm A*
Lecture 05 - Heuristic Search: A* and Beyond
Lecture 06 - Problem Reduction Search: AND/OR Graphs
Lecture 07 - Searching Game Trees: Shallow and Deep Pruning, Alpha-Beta Pruning
Lecture 08 - Knowledge Based Systems: Logic and Deduction
Lecture 09 - First Order Logic
Lecture 10 - Inference in First Order Logic
Lecture 11 - Resolution-Refutation Proofs
Lecture 12 - Resolution Refutation Proofs
Lecture 13 - Logic Programming: Prolog
Lecture 14 - Prolog Programming
Lecture 15 - Prolog: Exercising Control
Lecture 16 - Additional Topics: Constraint Logic Programming, Iterative Refinement Search, Memory Bounded Search, Multi-Objective Search
Lecture 17 - Introduction to Planning
Lecture 18 - Planning Algorithms: Partial Order Planning
Lecture 19 - Planning Algorithms: GraphPLAN and SATPlan
Lecture 20 - Planning Algorithms: SATPlan
Lecture 21 - Reasoning under Uncertainty
Lecture 22 - Bayesian Networks
Lecture 23 - Reasoning with Bayes Networks
Lecture 24 - Reasoning with Bayes Networks (cont.)
Lecture 25 - Reasoning under Uncertainty: Issues and Other Approaches
Lecture 26 - Learning: Decision Trees
Lecture 27 - Learning: Neural Networks
Lecture 28 - Back Propagation Learning