| 1 | Introduction and scope | |
| 2 | Reasoning: goal trees and problem solving | |
| 3 | Reasoning: goal trees and rule-based expert systems | |
| 4 | Search: depth-first, hill climbing, beam | Problem set 0 due |
| 5 | Search: optimal, branch and bound, A* | |
| 6 | Search: games, minimax, and alpha-beta | Problem set 1 due |
| | Quiz 1 | |
| 7 | Constraints: interpreting line drawings | |
| 8 | Constraints: search, domain reduction | |
| 9 | Constraints: visual object recognition | Problem set 2 due |
| 10 | Introduction to learning, nearest neighbors | |
| 11 | Learning: identification trees, disorder | |
| | Quiz 2 | |
| 12 | Learning: neural nets, back propagation | Problem set 3 due |
| 13 | Learning: genetic algorithms | |
| 14 | Learning: sparse spaces, phonology | |
| 15 | Learning: near misses, felicity conditions | |
| 16 | Learning: support vector machines | Problem set 4 due |
| | Quiz 3 | |
| 17 | Learning: boosting | |
| 18 | Representations: classes, trajectories, transitions | |
| 19 | Architectures: GPS, SOAR, Subsumption, Society of Mind | |
| 20 | The AI business | |
| 21 | Probabilistic inference I | |
| | Quiz 4 | |
| 22 | Probabilistic inference II | Problem set 5 due |
| 23 | Model merging, cross-modal coupling, course summary | |
