Acknowledgement and Citations: Some of the material below was developed from:
- The POGIL respository for Computer Science
- the Berkeley AI project
- Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
W | Date | Lecture Topic | Readings | Activities | Homework | Project |
---|---|---|---|---|---|---|
1 | 17-Jan |
|
Agents and Rationality | PA 1 | ||
2 | 22-Jan |
Uninformed Search BFS, DFS, IDS |
Uninformed Search | PA 2 | ||
24-Jan | Graph Search vs. Tree Search | Lab 1:Uninformed Search | ||||
3 | 29-Jan | Uniform Cost and A* Search | Informed Search | |||
31-Jan | Developing Heuristics | Lab 2: Informed Search | ||||
4 | 5-Feb |
Mastery Quiz 1a Local Search |
Local Search | PA 2 Due Feb 8 | ||
7-Feb | Using Local Search methods to Solve N-Queens | Lab 3: Local Search | ||||
5 | 12-Feb |
|
CSPs | PA 3 | ||
14-Feb |
CSPs
|
Lab 4: Min Conflicting Queeens | ||||
6 | 19-Feb |
Adversarial Search
|
Adversarial Search | |||
21-Feb | Expectimax, Utility Functions | Adversarial Search with Uncertainty | RQ 7 | |||
7 | 26-Feb | MPQW7 | ||||
28-Feb |
|
HW6 | ||||
8 | 4-Mar | Markov Decision Processes 1 | MDPs |
PA 3 Due Mar 5 (/pas/pacmanwithghosts/) |
||
6-Mar |
Master Quiz 2b Markov Decision Processes 2 |
|||||
9 | 11-Mar | Spring BREAK | ||||
13-Mar | Spring BREAK | |||||
10 | 18-Mar | MDP Lab 1 | Lab 6: Value Iteration | |||
20-Mar | Reinforcement Learning 1 | Reinforcement Learning | ||||
11 | 25-Mar | Reinforcement Learning 2 | Lab 7: Reinforcement Learning Crawler | |||
27-Mar | PA Work day | |||||
12 | 1-Apr |
|
Propositional Logic | PA 4 Due Apr 2 | ||
3-Apr | Theorm Proving and Resolution | |||||
13 | 8-Apr |
|
First Order Logic | |||
10-Apr | FOL Resolution and Chaining | |||||
14 | 15-Apr | Mastery Quiz 4 | Probability Review | |||
17-Apr | Bayes Representations | Bayes | ||||
15 | 22-Apr | Bayes Variable Elimination | ||||
24-Apr | Bayes Sampling | |||||
16 | 29-Apr | Hidden Markov Models | HMMs | |||
1-May |
|