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# CS 188 Summer 2023

## Syllabus

Wk. Date Lecture
(pptx files)
(AIMA, 4th ed.)
Discussion Homework Project
1Tue
Jun 20
1. Intro, Overview of AI, Rational Agents, Utilities and Lotteries
Slides
Ch. 1, 2
Note 1
1. Tower of Hanoi, Search Review
Worksheet / Solutions
Project 0 tutorial
(due Friday, June 23)
Wed
Jun 21
2. Uninformed Search, Informed search with Heuristics, Tree Search vs. Graph Search
Slides
Ch. 3
Note 2
2. Informed Search, Heuristics
Worksheet / Solutions
HW1
(due Fri, Jun 23)
Project 1 search
(due Tuesday, June 27)
Thu
Jun 22
3. Constraint Satisfaction, Forward Checking and Recursive Backtracking, Arc Consistency
Slides
6.1 - 6.3
Note 3
3. IDA*, Search Challenge Problems
Worksheet / Solutions
2Mon
Jun 26
4. Finish up CSPs, Local Search, Hill-Climbing and Simulated Annealing
Slides
6.4 - 6.5, 4.1 - 4.2
Note 4
4. CSPs, Local Search
Worksheet / Solutions
HW2
(due Fri, Jun 30)
Tue
Jun 27
5. Game Trees, Minimax, Alpha-beta pruning, Expectimax
Slides
5.1 - 5.3
Note 5
5. CSP Air Traffic, Game Trees
Worksheet / Solutions
Project 2
(due Wednesday, July 5)
Wed
Jun 28
6. Alpha-Beta Pruning, Expectimax, Monte Carlo Tree Search
Slides
5.4 - 5.5
Note 6
6. Pruning Practice, Challenge Problems
Worksheet / Solutions
Thu
Jun 29
7. Conditional Probability Review, Bayes Nets, Inference by Enumeration
Slides
14.1 - 14.2
Note 7
7. Probability Review, Simple Bayes Net
Worksheet / Solutions
Project 3
(due Tuesday, July 11)
3Mon
Jul 03
8. No class8. Variable Elimination, Representation
Worksheet / Solutions
HW3
(due Fri, July 7)
Tue
Jul 04
9. No class, Independence DayNo Discussion
Wed
Jul 05
10. D-Separation, Structure of Bayes Nets, Approximate inference with sampling14.49. D-Separation, Challenge Questions
Worksheet / Solutions
Project 4
(due Thursday, July 20)
Thu
Jul 06
11. Bayes Net Sampling, Markov Chain Monte Carlo14.510. Sampling in Bayes Nets, Review
Worksheet / Solutions
4Mon
Jul 10
12. Markov Chains Review, Mini-Forward Algorithm, Stationarity, HMMs, Forward Algorithm
Slides
15.1 - 15.6
Note 12
11. Markov Models, Forward Algorithm
Worksheet / Solutions
HW4
(due Fri, July 14)
Tue
Jul 11
13. HMMs, Forward Algorithm, Viterbi Algorithm, Particle Filtering15.1 - 15.612. Viterbi Algorithm, Particle Filtering
Worksheet / Solutions
Wed
Jul 12
14. Finish HMMs, Rational Preferences and Decision Networks
Slides
16.1 - 16.313. HMM Challenge Questions
Worksheet / Solutions
Thu
Jul 13
15. Decision Networks and VPI, Midterm Review
Slides
16.5 - 16.7
Note 15
Midterm Review Sections Project 5
(due Thursday, July 27)
5Mon
Jul 17
16. No Lecture: Midterm 7-9pm in Wheeler 15017.1 - 17.314. Decision Networks, VPI
Worksheet / Solutions
HW5
(due Mon, July 24)
Tue
Jul 18
17. MDPs, Policies, Values, Q-values, Dynamic Programming
Slides
17.1 - 17.3
Note 17
15. MDPs, Dynamic Programming
Worksheet / Solutions
Wed
Jul 19
18. Intro to Reinforcement Learning, Bandit Problems, Regret
Slides
22.1 - 22.6
Note 18
16. MDP Challenge Questions
Worksheet / Solutions
Thu
Jul 20
19. RL: Temporal Difference Learning, Q-learning22.1 - 22.617. Reinforcement Learning
Worksheet / Solutions
6Mon
Jul 24
20. Machine Learning: Learning from Data, Training/Validation/Test, MLE and MAP, Naive Bayes
Slides
20.1 - 20.2, 18.8
Note 20
18. Reinforcement Learning Part 2
Worksheet / Solutions
HW6
(due Fri, July 28)
Project 6
(due Saturday, August 5)
Tue
Jul 25
21. Machine Learning: Features, Linear Regression, Regularization and Ridge Regression18.619. ML Potpourri, MLE, Naive Bayes
Worksheet / Solutions
Wed
Jul 26
22. Optimization and Gradient Methods, Perceptron, Logistic Regression, MLP, Loss Functions
Slides
21.1 - 21.520. Vector Calculus Review, Linear Regression
Worksheet / Solutions
Thu
Jul 27
23. Neural Networks: Forward pass, Representationability
Slides
21.1 - 21.521. Perceptron, Logistic Regression Optimization
Worksheet / Solutions
7Mon
Jul 31
24. Optimization in Neural Networks: Backpropagation, Autodiff, Training
Slides
21.1 - 21.5
Note 24
22. Neural Network Representations
Worksheet / Solutions
HW7
(due Fri, Aug 4)
Tue
Aug 01
25. Learning Theory, Decision Trees, and Additional Optimization Methods
Slides
21.1 - 21.523. Neural Networks and Optimization
Worksheet / Solutions
Wed
Aug 02
26. Lecture Cancelled24. Backpropagation in Neural Networks
Worksheet / Solutions
Thu
Aug 03
Slides
25. Final Review Sections

Search/CSPs: Worksheet / Solutions
Games/VPI: Worksheet / Solutions
Bayes Nets: Worksheet / Solutions
HMMs: Worksheet / Solutions
MDP/RL: Worksheet / Solutions
Machine Learning: Worksheet / Solutions
Neural Networks: Worksheet / Solutions

8Mon
Aug 07