Instructors
[BW] = Prof. Brian Williams
[EF] = Prof. Emilio Frazzoli
[SK] = Sertac Karaman
| LEC # | TOPICS | LECTURE NOTES |
|---|---|---|
| 1 | Introduction [BW, EF] |
(PDF) |
| 2 | Foundations I: state space search [BW] | ( PDF) |
| 3 | Foundations II: complexity of state space search [BW] | (PDF) |
| 4 | Foundations III: soundness and completeness of search [SK] | (PDF) (Courtesy of Sertac Karaman. Used with permission.) |
| 5 | Constraints I: constraint programming [BW] | (PDF) |
| 6 | Constraints II: constraint satisfaction [BW] | (PDF) |
| 7 |
Constraints III: conflict-directed back jumping Introduction to operator-based planning [BW] |
( ( |
| 8 |
Planning I: operator-based planning and plan graphs Planning II: plan extraction and analysis [BW] |
( ( |
| 9 | Planning III: robust execution of temporal plans [BW] | ( PDF) (With contributions from Andreas Hofmann and Julie Shah. Used with permission.) |
| 10 | Model-based reasoning I: propositional logic and satisfiability [BW] | ( PDF) |
| 11 |
Model-based programming of robotic space explorers [BW] Encoding planning problems as propositional logic satisfiability [SK] |
( |
| Midterm exam | ||
| 12 | Model-based reasoning II: diagnosis and mode estimation [BW] |
( PDF 1 - 1.6MB) ( PDF 2 - 2.0MB)
|
| 13 | Model-based reasoning III: OpSat and conflict-directed A* [BW] | ( PDF) |
| 14 | Global path planning I: informed search [EF] | ( PDF) |
| 15 | Global path planning II: sampling-based algorithms for motion planning [EF] | ( PDF - 1.3MB) |
| 16 | Mathematical programming I [EF] | (PDF) |
| 17 | Mathematical programming II: the simplex method [EF] | ( PDF) |
| 18 | Mathematical programming III: (mixed-integer) linear programming for vehicle routing and motion planning [EF] | ( PDF) |
| 19 | Reasoning in an uncertain world [BW] |
( PDF 1) ( PDF 2)
|
| 20 | Inferring state in an uncertain world I: introduction to hidden Markov models [EF] | ( PDF) |
| 21 | Inferring state in an uncertain world II: hidden Markov models, the Baum-Welch algorithm [EF] | ( PDF) |
| 22 | Dynamic programming and machine learning I: Markov decision processes [EF] | ( PDF) |
| 23 | Dynamic programming and machine learning II: Markov decision processes, policy iteration [EF] | ( PDF) |
| 24 | Game theory I: sequential games [EF] | ( PDF) |
| 25 | Game theory II: differential games [SK] | ( PDF - 1.7MB) (Courtesy of Sertac Karaman. Used with permission.) |

