| Week # | Monday | Wednesday | Friday |
| 1 | Jan 5: Lecture (in MGH 231). Course introduction, definition of intelligence, Turing Test. Assignment 1 (Symbol manipulation in Python) given out. | Jan 7: Lecture (in MGH 231). Python functions; recursive functions on lists; lambda expressions; mapping; string operations. Example: Sequence prediction. | Jan 9: Lab (in MGH 044). Introduction to Python; interaction; function definition and calling; lists; |
| 2 | Jan 12: Lecture (in MGH 231). State-Space Search: Introduction | Jan 14: Lecture (in MGH 231). State-Space Search: Alpha-beta search with Tic-Tac-Toe. Checkers and Chess. | Jan 16: Lab (in MGH 044). Game playing. Assignment 1 due. Assignment 2 (State-space search) given out. |
| 3 | Jan 19: Martin Luther King Holiday (no class) | Jan 21: Lecture (in MGH 231). State-Space Search: Theory and Algorithms. | Jan 23: Lab (in MGH 044). Interactive State-Space Search. |
| 4 | Jan 26: Lecture (in MGH 231). Knowledge representation with ISA hierarchies. | Jan 28: Lecture (in MGH 231). Propositional logic, modus ponens, perfect induction, and resolution. | Jan 30: Lecture (in MGH 231). Predicate Logic. Definitions. Horn-clause resolution. Assignment 2 due. Assignment 3 (Logical reasoning) given out. |
| 5 | Feb 2: Lecture (in MGH 231). Predicate Logic, continued | Feb 4: Lecture (in MGH 231). Predicate Logic, continued | Feb 6: Lecture (in MGH 231). Agent reasoning with modal logic. |
| 6 | Feb 9: Lecture (in MGH 231). Probabilistic inference with Bayes' rule. Bayes' networks. Assignment 3 due. | Feb 11: Lecture (in MGH 231). Building Bayes nets. | Feb 13: Midterm 1 (in MGH 231). |
| 7 | Feb 16: Presidents Day Holiday (no class) | Feb 18: Lecture (in MGH 231). Introduction to vision: illusions; sampling and quantization, histograms, thresholding, the Hough transform. | Feb 20: Lab (in MGH 044). Image understanding. |
| 8 | Feb 23: Lecture (in MGH 231). Image understanding: edge detection, segmentation into regions; morphology. Assignment 4 (Developing AI Software) given out. | Feb 25: Lecture (in MGH 231). Image understanding: scene labeling, pattern recognition with perceptrons. | Feb 27: Lecture (in MGH 231). Neural networks and machine learning: perceptron training and backpropagation. Assignment 4 due. Begin projects. |
| 9 | Mar 2: Lab (in MGH 030). Expert systems using Horn clause resolution in PROLOG | Mar 4: Review session (in MGH 231). | Mar 6: Midterm 2 (in MGH 231). |
| 10 | Mar 9: Lecture (in MGH 231). Natural language understanding: context-free grammars and parsing. Semantic grammars and Semantics: Case frames. Augmented transition networks and the STONE WORLD program. | Mar 11: Lecture (in MGH 231). Big issues and the future of AI: common sense, ontologies, dangers of AI, Asimov's rules of robotics, hopes for AI. | Mar 13: Lab (in MGH 044). Presentations and Demos. Those who can come early are invited to arrive at 11:30, in order to have more time for presentations and feedback. |
| Mar 19 (Thursday): FINAL PROJECT DEMO SESSION 8:30-10:20 in MGH 044 |