CS165A (Spring 2022) Introduction to Artificial Intelligence |
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Piazza: https://piazza.com/ucsb/spring2022/cs165a/home
Piazza is our main channel of communication. Questions should be posted here.
Gradescope: https://www.gradescope.com/courses/381247
This is where you submit your project code and reports.
Office hours:
Instructor: 2 - 3 pm Thursday at Henley Hall 2013
TA: Dan Qiao, Office Hour: 2 - 3 pm Wednesday near Henley Hall 2118 .
Course evaluation:
15% each for the three Coding Projects, 25% Midterm, 30% Final.
Textbook: Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Pearson, Fourth Edition, 2020
Other reference books:
Sutton and Barto. Reinforcement learning: An introduction, MIT press, Second Edition, 2018.
| Tues and Thurs | Lectures | Reading materials | Project | Optional HW | Fridays | Recitation | |
|---|---|---|---|---|---|---|---|
| 1 | 29-Mar | Intro and course overview: Intelligent agents [Slides] | AIMA Ch.1, AIMA Ch. 2 | HW0 Foundations [pdf,data] | |||
| 2 | 31-Mar | Machine Learning I [Slides, Annotated] | AIMA Ch. 19, D2L Ch. 1 | 1-Apr | HW0 Discussion [Notes, Juypter notebook] | ||
| 3 | 5-Apr | Machine Learning II [Slides, Annotated] | AIMA Ch. 19, D2L Ch. 1 | Project 1 Out [StartupKit] | |||
| 4 | 7-Apr | Machine Learning III [Slides, Annotated] | D2L Ch. 3, CH. 4, CH. 11 | HW1 Machine Learning [pdf] | 8-Apr | Project help: Linear Logistic Regression [Notes, autograd example, vectorization] | |
| 5 | 12-Apr | Probabilistic Graphical models I [Slides, Annotated] | AIMA Ch. 12.1-12.6 | ||||
| 6 | 14-Apr | Probabilistic Graphical models II [Slides, Annotated] | AIMA Ch. 13.1-13.3, Jordan PGM Ch. 2.1 | 15-Apr | HW1 Discussion [Notes] | ||
| 7 | 19-Apr | Search: Solving Problems with Search [Slides, Annotated] | AIMA Ch. 3.1-3.4 | HW2 PGM and Search [pdf] | |||
| 8 | 21-Apr | Search: Search algorithms [Slides, Annotated] | AIMA Ch. 3.4-3.6 | Project 1 Due / Project 2 Out | 22-Apr | Project help: implementing search algorithms | |
| 9 | 26-Apr | Search: Games and Adversarial Search [Slides, Annotated] | AIMA Ch. 5.1-5.4 | ||||
| 10 | 28-Apr | Midterm Review [Slides, Annotated] | 29-Apr | HW2 Discussion / Midterm Q&A | |||
| 11 | 3-May | Midterm | HW3 Search and MDP [pdf] | ||||
| 12 | 5-May | RL: Introduction + Markov Decision Processes [Slides, Annotated] | Sutton and Barto: Ch 1, AIMA: Ch 17.1, 17.2 | 6-May | Understanding Markov Decision Processes | ||
| 13 | 10-May | RL:Markov Decision Processes [Slides, Annotated] | AIMA: Ch 17.1, 17.2, 17.3. Sutton and Barto: Ch 3 | ||||
| 14 | 12-May | RL:Bandits problems and Exploration [Slides, Annotated] | Sutton and Barto: CH 2, AIMA Ch 22.4 | Project 2 Due / Project 3 Out | 13-May | HW3 Discussion | |
| 15 | 17-May | RL:Reinforcement Learning algorithms I [Slides, Annotated] | AIMA Ch 22.1-22.3, Sutton and Barto: Ch 5-6 | HW4 RL and Logic [pdf] | |||
| 16 | 19-May | RL:Reinforcement Learning algorithms II [Slides, Annotated] | AIMA Ch 22.4, Sutton and Barto: Ch 9.1-9.4, Ch 13.1-13.3 | 20-May | Project help: Implementing RL algorithms | ||
| 17 | 24-May | Logic I: Logic intro & Propositional logic [Slides] | AIMA Ch 7, Ch 8 | ||||
| 18 | 26-May | Logic II: First order Logic [Slides, Annotated] | AIMA Ch 8, Ch. 9.1 | 27-May | HW4 Discussion | ||
| 19 | 31-May | Responsible AI: Challenges in Privacy, Fairness and Safety [Slides, Annotated] | AIMA Ch 1.5, AIMA Ch 27.3, Ch 28 | ||||
| 20 | 2-Jun | Final Review [Slides, Annotated] | Project 3 Due | 3-Jun | Q&A before the final | ||
| 21 | 6-Jun | Final Exam |