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] |
(PDF) (With contributions from Patrick Prosser. Used with permission.) (PDF) (With contributions from David Smith. Used with permission.) |
8 |
Planning I: operator-based planning and plan graphs Planning II: plan extraction and analysis [BW] |
(PDF) (With contributions from Maria Fox. Used with permission.) (PDF) (With contributions from Maria Fox. Used with permission.) |
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] |
(PDF) (Courtesy of Sertac Karaman. Used with permission.) |
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.) |