CS 188 | Introduction to Artificial Intelligence

Fall 2020

Lectures: Tu/Th 5:00–6:30 pm Online

CS188 Robot Waving

Description

This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm.

By the end of this course, you will have built autonomous agents that efficiently make decisions in fully informed, partially observable and adversarial settings. Your agents will draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial intelligence problems and will serve as the foundation for further study in any application area you choose to pursue.

See the syllabus for slides, deadlines, and the lecture schedule. Readings refer to AIMA unless otherwise specified.


Syllabus

Lecture topics subject to change as we begin the semester.
W Date Lecture Topic Readings Section Homework Project
0 Th 8/27 1. Intro to AI
pptx , pdf , recording
Ch. 1 & 2 N/A HW0 Math Diagnostic
Electronic
(Due 9/2 11:59 pm)
P0 Tutorial
(Due 8/31 11:59 pm)

1 Tu 9/1 2. Uninformed Search
pptx, pdf , recording
Ch. 3.1–3.4
Note 1
Section 0
Solns,
Andrea Rec. Regular
Katherine Rec. Regular
HW1 Search
Electronic
(Due 9/08 10:59 pm)
Written Homework 1 PDF
(Due 9/16 10:59 pm)
P1 Search
(Due 9/11 11:59 pm)

Mini-Contest 1
(Due 9/27 11:59 pm)
Th 9/3 3. A* Search and Heuristics
pptx, pdf , recording
Ch. 3.5–3.6
2 Tu 9/8 4. CSP I
pptx, pdf , recording
Ch 6.1
Note 2
Section 1
Reg Solns, Reg. Recorded 1 (Andrea)
Reg. Recorded 2 (Katherine)
Exam prep 1
Exam Prep Solns,
Exam Prep Recording
HW2 CSPs
Electronic
(Due 9/14 10:59 pm)


Th 9/10 5. CSP II
pptx, pdf , recording
Ch 6.2-6.5
3 Tu 9/15 6. Search with Other Agents I
pptx, pdf, recording
Ch. 5.2-5.5
Note 3
Section 2
Reg. solns, Recording 1: Katherine,
Recording 2: Andrea.
Exam prep 2
Exam Prep. solns, Exam Prep Recording
HW3 Games
Electronic
(Due 9/21 10:59 pm)
P2 Multiagent
(Due 9/25 11:59 pm)

Mini-Contest 2
(Due 10/30 11:59 pm)
Th 9/17 7. Search with Other Agents II
pptx, pdf, recording
Ch. 5.2-5.5,
Ch. 16.1-16.3
4 Tu 9/22 8. MDPs I
pptx, pdf, recording
Ch 17.1-3
Note 4
Section 3
Reg. Solns, Recording Katherine, Recording Andrea
Exam prep 3
Exam Prep. Solns, Exam Prep. Recording
HW4 MDPs
Electronic
(Due 9/28 10:59 pm)
Written HW2
PDF
(Due 10/07 10:59pm)
Th 9/24 9. MDPs II
pptx, pdf recording
Ch 17.1-3,
Sutton and Barto Ch. 3 & 4
5 Tu 9/29 10. RL I
pptx, pdf, Recording
Ch. 21,
Sutton and Barto Ch. 6.1, 6.2 & 6.5
Note 5
Section 4
Solutions, Recording Katherine, Recording Andrea

Exam Prep 4
Exam Prep Solns, Recording
P3 RL
(Due 10/09 11:59 pm)
Th 10/1 11. RL II
pptx, pdf, recording
Ch. 21
6 Tu 10/6 12. RL III
pptx, pdf, Recording
Ch. 21 Section 5
Reg. Solns., Recording Andrea, Recording Katherine

Exam prep 5
Solutions, Recording
HW5 RL
Electronic
(Due 10/12 10:59 pm)
Th 10/8 13. Probability + BN: Intro
pptx, pdf, recording
Ch 13.1-13.5
Note 6
7 Tu 10/13 14. BN: Representation
pptx, pdf recording
Ch. 14.1, 14.2, 14.4 Midterm Review - Search -- Solns
Midterm Review - CSP -- Solns
Midterm Review - Games -- Solns
Midterm Review - MDPs -- Solns
Midterm Review - RL -- Solns
Th 10/15 Midterm (5-7pm)
8 Tu 10/20 15. BNs: Inference
pptx, pdf Recording
Ch. 14.4 Section 6
Solutions, Rec. Katherine, Rec. Andrea

Exam Prep 6
Exam Prep Solutions, Recording
HW 6 Electronic (Due 10/26 10:59pm)
Th 10/22 16. BN: Independence
pptx, pdf, recording
Ch. 14.1, 14.2, 14.4
9 Tu 10/27 17. BN: Sampling
pptx, pdf, recording
Ch. 14.4–14.5 Section 7
Solns, Recording Katherine, Recording Andrea,

Exam prep 7 Prep Solns, Recording
HW 7Electronic (Due 11/02 10:59pm)
Written HW 3
PDF
Due Friday 11/06 10:59PM.
P4 Tracking
(Due 11/13 11:59 pm)
Th 10/29 18. Decision Networks / VPI
archive pptx, archive pdf
Ch. 16.5-16.6
Note 7
10 Tu 11/3 19. HMMs
archive pptx, archive pdf
Ch. 15.2-15.6
Note 8


Th 11/5 20. Particle Filtering
archive pptx, archive pdf
Ch. 15.2, 15.6
11 Tu 11/10 21. ML: Naive Bayes
archive pptx, archive pdf
Ch. 20.1-20.2.2
Note 9
Th 11/12 22. ML: Perceptrons and Logistic Regression
archive pptx, archive pdf
Ch. 18.6.3 & 18.8
12 Tu 11/17 23. ML: Optimization and Neural Networks
archive pptx, archive pdf
Ch. 18.6.3 & 18.8
Note 10
Th 11/19 24. ML: Neural Networks II and IRL
archive pptx, archive pdf
Ch 18.3, 18.7
13 Tu 11/24 Thanksgiving Break N/A
Th 11/26 Thanksgiving Break
14 Tu 12/1 25. Advanced Topics
archive pptx, archive pdf
Th 12/3 26. Advanced Topics
15 Tu 12/8 RRR Week
Th 12/10 RRR Week
16 Tu 12/15 Finals Week N/A
Wed 12/16 Final Exam (11:30am - 2:30pm)