Detailed Syllabus
- 14 JAN: Lecture #01: Course Mechanics / Topics / Background /
History [R&N 1.1, 3-4]
- 16 JAN: Lecture #02: The Turing Test
[R&N 26.1-2; Turing's Turing Test Article]
- 21 JAN: MARTIN LUTHER KING JR. HOLIDAY (No Class)
- 23 JAN: Lecture #03: Intelligent Agents 1; Problem Set #1 Due
[R&N 2.1-4]
- 28 JAN: Lecture #04: Intelligent Agents 2
[Braitenberg's Vehicles, pp. 1-42]
- 30 JAN: Lecture #05: Solving Problems by Searching; Problem Set #2 Due
[3.1-4]
- 04 FEB: Lecture #06: Heuristic Search [3.5-6, 4.1-2]
- 06 FEB: Lecture #07: Local Search; Problem Set #3 Due [4.3 plus box on Page 120]
- 11 FEB: Lecture #08: Constraint Satisfaction Problems [5.1, 2 (but
only through "forward Checking", p. 144), 3]
- 13 FEB: Lecture #09: Adversarial Search 1; Problem Set #4 Due [6.1-3]
- 18 FEB: Lecture #10: Adversarial Search 2 [6.4-7]
- 20 FEB: Lecture #11: Predicate Logic and Knowledge Representation; Problem Set #5 Due [7.1-4]
- 25 FEB: Lecture #12: Reasoning and Logical Agents [7.5-7]
- 27 FEB: Lecture #13: STRIPS Planning; Problem Set #6 Due [11.1, 2, 4]
- 03 MAR: Lecture #14: Planning and Acting in the Real World [12.1 (skim), 3, and 7] / Midterm Review; Mini PS #1 Due
- 05 MAR: Lecture #15: MIDTERM EXAM [Covers: all lectures and assigned
reading above; PS1-6; Mini PS1]
- 10 MAR: SPRING BREAK (No Class)
- 13 MAR: SPRING BREAK (No Class)
- 17 MAR: Lecture #16: Uncertainty [13]
- 19 MAR: Lecture #17: Probabilistic Reasoning 1; Problem Set #7 Due [14.1-4]
- 24 MAR: Lecture #18: Probabilistic Reasoning 2 [14.5, 7]
- 26 MAR: Lecture #19: Learning 1; Problem Set #8 Due [18.1-3]
- 31 MAR: Lecture #20: Learning 2 [18.4-5, 19.1]
- 02 APR: Lecture #21: Statistical Learning Methods 1; Problem Set #9 Due [20.1-3]
- 07 APR: Lecture #22: Statistical Learning Methods 2 [20.4-7]
- 09 APR: Lecture #23: Making Simple Decisions; Problem Set #10 Due [16.1-3, 4 (only through the end of Dominance), 5]
- 14 APR: Lecture #24: Making Complex Decisions [17.1, 2 (skip subsection on Convergence), 3]
- 16 APR: Lecture #25: Reinforcement Learning 1; Problem Set #11 Due [21.1-3]
- 21 APR: Lecture #26: Reinforcement Learning 2 [21.4-5]
- 23 APR: Lecture #27: Game Theory; Problem Set #12 Due [17.6, 7]
- 28 APR: Lecture #28: Final Review / Cleanup;
Mini PS #2 Due
- 30 APR: 491 Final Project Presentations
- 06 MAY: FINAL EXAM (8:30-11:30AM) [Covers: Entire Course]
Created: 2008-01-12.
Last Modified: 2008-01-13. © Michael S. Branicky