CS165A: Artificial Intelligence (Fall 2020)


Instructor: Prof. Yu-Xiang Wang

TA1: Xuandong Zhao
TA2: Kaiqi Zhang
TA3: Benu Changmai

Syllabus: Please read this carefully.

Lecture Section: Tuesday/Thursday 12:30-1:45pm Location: Zoom (link on Piazza)
Discussion Section 1: Wed 5:00-5:50pm, Location: Zoom (link on Piazza)
Discussion Section 2: Wed 6:00-6:50pm, Location: Zoom (link on Piazza)
Discussion Section 3: Wed 7:00-7:50pm, Location: Zoom (link on Piazza)

Piazza: piazza.com/ucsb/fall2020/cs165a
Piazza is our main channel of communication. Questions should be posted here.

Gradescope: [ link]
We will be collecting homework submissions via Gradescope. You should have been added to the course via your UCSB email.

Office hours: Instructor Office Hour: Thursday 2:00-3:00pm
TA1: Xuandong Zhao, Office Hour: Wednesday 4-5 pm.
TA2: Kaiqi Zhang, Office Hour: Friday 5-6 pm.
TA3: Benu Changmai, Office Hour: Thursday 4-5 pm.

All office hours are on the same Zoom link (shared on Piazza) unless otherwise instructed.

Textbook: Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, Third Edition, 2010
If you bought the new 4th Edition, that works perfectly too.

Other reference books:

Course Schedule / Lecture Notes

Week Date Topic Reading Assignment
1 1-Oct Course Overview + Intelligent Agents AIMA Ch.1, AIMA Ch. 2 HW1 out
2 6-Oct Machine Learning [annotated] AIMA Ch. 18 (Ch. 19 in 4th edition), D2L Ch. 1, ESL Ch. 1
8-Oct Machine Learning [annotated] AIMA Ch. 18 (Ch. 19 in 4th edition), D2L Ch. 1, ESL Ch. 1
3 13-Oct Machine Learning [annotated] D2L Ch. 3, CH. 4, CH. 11
15-Oct Probabilistic Graphical Models [annotated] AIMA Ch. 13 (Ch. 12 in 4th edition) HW2 Out
4 20-Oct Probablistic Graphical Models [annotated] AIMA Ch. 14 (Ch. 13 in 4th edition), Jordan PGM Ch. 2.1 HW1 Due
22-Oct Search: Solving Problems with Search [annotated] AIMA Ch. 3.1-3.4
5 27-Oct Search: Search algorithms [annotated] AIMA Ch. 3.4-3.6
29-Oct Search: Adversarial Search [annotated] AIMA Ch. 5.1-5.4
6 3-Nov Midterm Review [annotated] HW2 Due
5-Nov Midterm HW3 out
7 10-Nov RL: Introduction and Markov Decision Processes [annotated] Sutton and Barto: Ch 1, AIMA: Ch 17.1, 17.2
12-Nov RL: Markov Decision Processes [annotated] AIMA: Ch 17.1, 17.2, 17.3. Sutton and Barto: Ch 3
8 17-Nov RL: Bandits Problems and Exploration [annotated] Sutton and Barto: CH 2, AIMA Ch 21.4 (Ch 22.4 in 4th edition)
19-Nov RL: Reinforcement learning algorithms [annotated] AIMA Ch. 21.1-21.3 (Ch 22.1-22.3 in 4th edition) Sutton and Barto: Ch 4-6, Ch 13 HW4 out
9 24-Nov RL: Reinforcement learning algorithms AIMA Ch. 21.1-21.3 (Ch 22.1-22.3 in 4th edition) Sutton and Barto: Ch 4-6, Ch 13 HW3 due
26-Nov Thanksgiving holiday / no class AIMA: Ch 7
10 1-Dec Logic: Logic intro & Propositional Logic AIMA Ch 7, Ch 8
3-Dec Logic: First order logic AIMA Ch. 8, Ch. 9
11 8-Dec Responsible AI HW4 due
10-Dec Final review
14-Dec Final Exam. Take-home

Other Course Material