| 1 |
Introduction to Principles of Autonomy and Decision Making
Jump Starting With Scheme |
AIMA. Chapters 1 and 2. |
| 2 |
Some Scheme |
"Teach Yourself Scheme in Fixnum Days." (PDF) |
| 3 |
Rule-based Systems |
AIMA. Chapters 9.2-9.4. |
| 4 |
Problem Solving as State Space Search |
AIMA. Chapter 3. |
| 5 |
Analysis of Uninformed Search Methods
Some More Scheme |
AIMA. Chapter 3. |
| 6 |
Even More Scheme |
"Teach Yourself Scheme in Fixnum Days." (PDF) |
| 7 |
Constraint Satisfaction Problems: Formulations
Solving Constraint Satisfaction Problems: Arc Consistency and Constraint Propagation |
AIMA. Chapters 5 and 24.4 (pp. 881-884). |
| 8 |
Solving Constraint Satisfaction Problems: Forward Checking
Propositional Logic and Satisfiability |
AIMA. Chapters 5 and 6. |
| 9 |
Propositional Logic and Satisfiability (cont.) |
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| 10 |
Graph-based Planning |
AIMA. Chapter 11. |
| 11 |
Partial Order Planning and Execution |
AIMA. Chapter 12. |
| 12 |
Mid-term Exam |
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| 13 |
Programming SATPlan |
AIMA. Chapter 7. |
| 14 |
Roadmap Path Planning
Shortest Path and Informed Search |
AIMA. Chapter 25.4.
AIMA. Chapter 4.1-2.
Introduction to Algorithms, 2nd Edition, by Cormen, Leiserson, Rivest, and Stein. Chapters 25.1-2. |
| 15 |
Shortest Path and Informed Search (cont.) |
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| 16 |
Model-based Diagnosis |
AIMA. Chapters 4.1-2 and 25.4. |
| 17 |
Model-based Diagnosis (new slides) |
AIMA. Chapter 6. |
| 18 |
Introduction to Linear Programming |
Handouts:
AMPL (PDF)
Steel (PDF) |
| 19 |
Spacecraft Rendezvous and Rover Path Planning Using Linear Programs |
Handout:
Linear Programming Example |
| 20 |
Basis Theory |
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| 21 |
Integer Programming and Branch and Bound |
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| 22 |
16.413 Project Group Meetings |
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| 23 |
Particle Filters for Fun and Profit |
AIMA. Chapter 6. |
| 24 |
Student Presentations |
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| 25 |
Learning to Act Optimally: Reinforcement Learning
Planning to Maximize Reward: Markov Decision Processes |
AIMA. Chapter 6. |
| 26 |
Principles of Autonomy and Decision Making |
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| 27 |
Final Exam |
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