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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 nptel.ac.in)

Lecture 13 - Logic Programming: Prolog

Go to the Course Home or watch other lectures:

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