| Day |
Topic |
Reading |
Slides |
Out |
Due |
| Tu 8/28 |
Introduction to AI |
Ch. 1, 2 (both general) |
2PP
6PP
|
Python Tutorial |
9/4 |
| Th 8/30 |
Agents and Search |
Ch. 3 |
2PP
6PP
|
Pacman: Search |
9/12 |
| Tu 9/4 |
A* Search and Heuristics |
Ch. 4.1-2 |
2PP
6PP
|
|
|
| Th 9/6 |
Constraint Satisfaction Problems |
Ch. 5.1 |
2PP
6PP
|
|
|
| Tu 9/11 |
CSPs II |
Ch. 5.2-4 |
2PP
6PP
|
|
|
| Th 9/13 |
Robot Motion |
Ch. 25.4 |
2PP
6PP
|
Pacman: Adversarial |
10/1 |
| Tu 9/18 |
Game Trees: Minimax |
Ch. 6.2-5 |
2PP
6PP
|
|
|
| Th 9/20 |
Game Trees: Expectimax |
Ch. 6.2-5 |
2PP
6PP
|
|
|
| Tu 9/25 |
Utilities / MEU |
Ch. 16.1-3 |
2PP
6PP
|
|
|
| Th 9/27 |
Markov Decision Processes |
Sutton
and Barto Ch. 3-4 |
2PP
6PP
|
MDPs & RL |
10/11 |
| Tu 10/2 |
MDPs II |
Ch. 17.1-3, Sutton
and Barto Ch. 6.1,2,5 |
2PP
6PP
|
|
|
| Th 10/4 |
Reinforcement Learning |
|
2PP
6PP
|
|
|
| Tu 10/9 |
Reinforcement Learning II |
|
2PP
6PP
|
|
|
| Th 10/11 |
Probability |
Ch. 13.1-6 |
2PP
6PP
|
|
|
| Tu 10/16 |
MIDTERM EXAM (in
class) |
|
|
|
|
| Th 10/18 |
Bayes' Nets I |
Ch. 14.1-2,4 |
2PP
6PP
|
|
|
| Tu 10/23 |
Bayes' Nets II |
Ch. 14.3, Jordan
2.1 |
2PP
6PP
|
|
|
| Th 10/25 |
Bayes' Nets III |
Ch. 14.4-5 |
2PP
6PP
|
|
|
| Tu 10/30 |
Bayes' Nets IV |
Ch. 14.4-5 |
2PP
6PP
|
Static Battleship |
11/12 |
| Th 11/1 |
Decision Diagrams |
Ch. 15.1-3,6 |
2PP
6PP
|
|
|
| Tu 11/6 |
HMMs: Monitoring |
Ch. 15.2,5 |
2PP
6PP
|
Dynamic Battleship |
11/19 |
| Th 11/8 |
HMMs: Particle Fitlering |
Ch. 15.2,6 |
2PP
6PP
|
|
|
| Tu 11/13 |
Speech, Viterbi, POMDPs |
Ch. 15.2,6 |
2PP
6PP
|
|
|
| Th 11/15 |
ML: Naive Bayes |
|
2PP
6PP
|
|
|
| Tu 11/20 |
ML: Perceptrons |
|
2PP
6PP
|
|
|
| Th 11/22 |
No Class |
| Tu 11/27 |
ML: Kernels |
|
2PP
6PP
|
Classification |
12/6 |
| Th 11/29 |
ML: Clustering |
|
2PP
6PP
|
|
|
| Tu 12/4 |
Language and Vision |
|
|
|
|
| Th 12/6 |
Advanced Topics and Pacman Contest |
|
|
|
|
| W 12/19 |
FINAL EXAM |
|
|
|
|
