6.034 Artificial Intelligence
6.034 Artificial Intelligence (Fall 2010, MIT OCW). Instructor: Professor Patrick Henry Winston. This course introduces students to the basic knowledge representation,
problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to
concrete computational problems; understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering; and appreciate the role of
problem solving, vision, and language in understanding human intelligence from a computational perspective.
(from ocw.mit.edu)
| Lecture 01 - Introduction and Scope |
| Lecture 02 - Reasoning: Goal Trees and Problem Solving |
| Lecture 03 - Reasoning: Goal Trees and Rule-Based Expert Systems |
| Lecture 04 - Search: Depth-First, Hill Climbing, Beam |
| Lecture 05 - Search: Optimal, Branch and Bound, A* |
| Lecture 06 - Search: Games, Minimax, and Alpha-Beta |
| Lecture 07 - Constraints: Interpreting Line Drawings |
| Lecture 08 - Constraints: Search, Domain Reduction |
| Lecture 09 - Constraints: Visual Object Recognition |
| Lecture 10 - Introduction to Learning, Nearest Neighbors |
| Lecture 11 - Learning: Identification Trees, Disorder |
| Lecture 12 - Learning: Neural Nets, Back Propagation |
| Lecture 13 - Learning: Genetic Algorithms |
| Lecture 14 - Learning: Sparse Spaces, Phonology |
| Lecture 15 - Learning: Near Misses, Felicity Conditions |
| Lecture 16 - Learning: Support Vector Machines |
| Lecture 17 - Learning: Boosting |
| Lecture 18 - Representations: Classes, Trajectories, Transitions |
| Lecture 19 - Architectures: GPS, SOAR, Subsumption, Society of Mind |
| Lecture 20 |
| Lecture 21 - Probabilistic Inference I |
| Lecture 22 - Probabilistic Inference II |
| Lecture 23 - Model Merging, Cross-Modal Coupling, Course Summary |
| References |
Artificial Intelligence (Fall 2010)
Instructor: Professor Patrick Henry Winston. Readings. Recitation Videos. Tutorials. Exams (no solutions). Assignments (no solutions). This course includes interactive demonstrations.
|