| 1 |
Introduction to Principles of Autonomy and Decision Making (PDF - 1.4 MB)
Jump Starting With Scheme (PDF) |
| 2 |
Some Scheme (PDF) |
| 3 |
Rule-based Systems (PDF) |
| 4 |
Problem Solving as State Space Search (PDF) |
| 5 |
Analysis of Uninformed Search Methods (PDF)
Some More Scheme (PDF) |
| 6 |
Even More Scheme (PDF) |
| 7 |
Constraint Satisfaction Problems: Formulation (PDF)
Solving Constraint Satisfaction Problems: Arc Consistency and Constraint Propagation (PDF) |
| 8 |
Solving Constraint Satisfaction Problems: Forward Checking (PDF)
Propositional Logic and Satisfiability (PDF) |
| 9 |
Propositional Logic and Satisfiability (cont.) (PDF) |
| 10 |
Graph-based Planning (PDF) |
| 11 |
Partial Order Planning and Execution (PDF) |
| 12 |
Mid-term Exam |
| 13 |
Programming SATPlan (PDF) |
| 14 |
Roadmap Path Planning (PDF)
Shortest Path and Informed Search (PDF) |
| 15 |
Shortest Path and Informed Search (cont.) (PDF) |
| 16 |
Model-based Diagnosis (PDF) |
| 17 |
Model-based Diagnosis (cont.) (PDF) |
| 18 |
Introduction to Linear Programming (PDF) |
| 19 |
Spacecraft Rendezvous and Rover Path Planning Using Linear Programs |
| 20 |
Basis Theory (PDF) |
| 21 |
Integer Programming and Branch and Bound (PDF) |
| 22 |
16.413 Project Group Meetings |
| 23 |
Particle Filters for Fun and Profit (PDF 1 - 1.7 MB) (PDF 2 - 2.4 MB) (PDF 3 - 1.9 MB) Courtesy of Nicholas Roy. |
| 24 |
Student Presentations |
| 25 |
Planning to Maximize Reward: Markov Decision Processes (PDF)
Learning to Act Optimally: Reinforcement Learning (PDF) |
| 26 |
Principles of Autonomy and Decision Making (PDF) |
| 27 |
Final Exam |