CS372 - Artificial Intelligence
Fall 2023
Administrivia
- Instructor: Phillip Kirlin
- Office hours: Mondays 1-2, Tuesdays 12:30-2, Wednesdays 3-4:30, Thursdays 2-3. Also available by appointment and over Slack.
- Canvas page: Use for grades and online assignment submissions.
- Syllabus and additional policies.
Resources
Calendar
- Thu, Aug 24
- Introduction and agents
Slides- Reading AIMA chapters 1 and 2
- Tue, Aug 29
- State Space Search I
Terminology, problem setup
Slides- Reading AIMA 3.1-3.3
- Thu, Aug 31
- State Space Search II
Uninformed search
Slides
Handouts: map, algorithms- Reading AIMA 3.4
- Tue, Sep 5
- State Space Search III
Informed search, A* algorithm
Slides
Handouts: notes- Reading AIMA 3.5
- Thu, Sep 7
- Adversarial Search I
Minimax algorithm
Slides
Handouts: minimax algorithm
Project 1, due Tue, Sep 19
Homework 1, due Thu, Sep 14- Reading AIMA 5.1-5.2 (through minimax)
- Tue, Sep 12
- Adversarial Search II
Alpha-beta pruning
Slides- Reading AIMA 5.2 (alpha-beta pruning)
- Thu, Sep 14
- Adversarial Search III
Alpha-beta with heuristics
Slides- Reading AIMA 5.3
- Tue, Sep 19
- Probability I
Terms and definitions- Reading AIMA 12.1-12.3
- Thu, Sep 21
- Probability II
Rules of probability
Project 2, due Thu, Oct 5
Homework 2, due Thu, Sep 28- Reading AIMA 12.4-12.5
- Tue, Sep 26
- Bayes nets I
- Reading AIMA 13.1-13.2
- Thu, Sep 28
- Bayes nets II
Exact inference- Reading AIMA 13.3
- Tue, Oct 3
- Bayes nets III
- Thu, Oct 5
- Statistical inference
Slides
Homework 3, due Fri, Oct 13- Reading (use slides)
- Tue, Oct 10
- Statistical inference
Project 3, due Thu, Oct 11
Slides- Reading (use slides)
- Thu, Oct 12
- Naive Bayes classifiers
Slides- Reading (use slides)
- Tue, Oct 17
- Fall break
- Thu, Oct 19
- Naive Bayes classifiers and review
- Reading (use slides)
- Tue, Oct 24
- Midterm
- Thu, Oct 26
- Markov chains
Slides
Notes - Tue, Oct 31
- Hidden Markov models
(see above for slides) - Thu, Nov 2
- Hidden Markov models
(see above for slides) - Tue, Nov 7
- Reinforcement learning
Slides
Notes - Thu, Nov 9
- Reinforcement learning
(see above for slides) - Tue, Nov 14
- Reinforcement learning
(see above for slides) - Thu, Nov 16
- Neural networks
Slides
Perceptron learning solutions - Tue, Nov 21
- Guest lecture
- Thu, Nov 23
- Thanksgiving break
- Tue, Nov 28
- Neural networks
(see above for slides) - Thu, Nov 30
- Neural networks
(see above for slides) - Tue, Dec 5
- Wrapup