CS 188 | Introduction to Artificial Intelligence
Spring 2019
Lecture: M/W 5:00-6:30 pm, Wheeler 150
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
Wk | Date | Lecture Topic | Readings | Section | Homework | Project |
---|---|---|---|---|---|---|
0 | 1/23 Wed |
Intro to AI
(Slides: PDF — Video) |
Ch. 1 & 2 Note 1 |
N/A |
HW0 Math Diagnostic
[Electronic] (Due 1/28 11:59 pm) |
P0 Tutorial
(Due 1/28 4 pm) |
1 | 1/28 Mon |
Uninformed Search
(Slides: PDF, PPTX — Video) |
Ch. 3.1-3.4 | Section 1 (video) (without solutions) |
HW1 Search
[Electronic] [Written] (Due 2/4 11:59 pm) [Written solutions] |
|
1/30 |
A* Search and Heuristics
(Slides: PDF, PPTX — Video) |
Ch. 3.5-3.6 | ||||
2 | 2/4 Mon |
Game Trees
(Slides: PDF, PPTX — Video) |
Ch. 5.2-5.5, Ch. 16.1-16.3 Note 2 |
Section 2 (video) (without solutions) |
HW2 Game Trees
[Electronic] [Written] (Due 2/11 11:59 pm) [Written solutions] |
P1 Search
(Due 2/8 4 pm) Mini-Contest 1 (Due 2/11 11:59 pm) |
2/6 Wed |
MDPs I
(Slides: PDF, PPTX — Video) |
Ch. 17.1-17.3 Note 3 |
||||
3 | 2/11 Mon |
MDPs II
(Slides: PDF, PPTX — Video) |
Ch. 17.1-17.3, Sutton and Barto Ch. 3 & 4 | Section 3 (video) (without solutions) |
HW3 MDPs
[Electronic] [Written] (Due 2/18 11:59 pm) [Written solutions] |
|
2/13 Wed |
RL I
(Slides: PDF, PPTX — Video) |
Ch. 21, Sutton and Barto Ch. 6.1, 6.2 & 6.5 Note 4 |
||||
4 | 2/18 Mon | Holiday | Section 4 (video) (without solutions) |
HW4 RL
[Electronic] [Written] (Due 2/25 11:59 pm) [Written solutions] |
P2 Games
(Due 2/22 4 pm) Mini-Contest 2 (Due 3/11 11:59 pm) |
|
2/20 Wed |
RL II
(Slides: PDF — Video) |
Ch. 21 | ||||
5 | 2/25 Mon |
CSPs I
(Slides: PDF, PPTX — Video) |
Ch 6.1 Note 5 |
Section 5 (video) (without solutions) |
HW5 CSPs
[Electronic] [Written] (Due 3/4 11:59 pm) [Written solutions] |
|
2/27 Wed |
CSPs II
(Slides: PDF, PPTX — Video) |
Ch 6.2-6.5 | ||||
6 | 3/4 Mon |
Propositional Logic
(Slides: PDF, PPTX — Video) |
Ch 7 (7.5.2 and 7.6.2 are optional) Note 11 |
Section 6 (video) (without solutions) |
HW6 Logic
[Electronic] [Written] (Due 3/11 11:59 pm) [Written solutions] |
P3 RL
(Due 3/8 4 pm) |
3/6 Wed |
First-Order Logic
(Slides: PDF, PPTX — Video) |
Ch 8.1-8.3, 9.1-9.3 | ||||
7 | 3/11 Mon |
Probability
(Slides: PDF, PPTX — Video) |
Ch 13.1-13.5 |
Midterm Review CSP (no soln ) Games (no soln ) Logic (no soln ) RL (no soln ) Search (no soln ) |
HW7 Probability
[Electronic] [Written] (Due 4/1 11:59 pm) [Written solutions] |
|
3/13 Wed |
Bayesian Networks: Representation
(Slides: PDF, PPTX — Video) |
Ch 14.1, 14.2 & 14.4 Note 6 |
||||
8 | 3/18 Mon |
Bayesian Networks: Inference
(Slides: PDF, PPTX — Video) |
Ch 14.4 | Section 7 (video) (without solutions) |
HW8 Bayes Nets
[Electronic] [Written] (Due 4/8 11:59 pm) [Written solutions] |
|
3/20 Wed | Midterm (7 - 9 pm) (Midterm Prep) (Practice Midterm, no soln) | |||||
9 | 3/25 Mon | Spring Break | N/A | |||
3/27 Wed | Spring Break | |||||
10 | 4/1 Mon |
Bayesian Networks: Sampling
(Slides: PDF, PPTX — Video) |
Ch 14.4-14.5 | Section 8 (video) (without solutions) |
P4 Bayesian Networks and Hidden Markov Models
(Due 4/12 4 pm) |
|
4/3 Wed |
Hidden Markov Models
(Slides: PDF, PPTX — Video) |
Ch. 15.2-15.6 Note 8 |
||||
11 | 4/8 Mon |
Particle Filtering
(Slides: PDF, PPTX — Video) |
Ch. 15.2-15.6 Note 8 |
Section 9 (video) (without solutions) |
HW9 Bayes Nets and HMMs
[Electronic] [Written] (Due 4/15 11:59 pm) [Written solutions] |
|
4/10 Wed |
Decision Networks / Value of Perfect Information
(Slides: PDF, PPTX — Video) |
Ch. 16.5-16.6 Note 7 |
||||
12 | 4/15 Mon |
Machine Learning: Naive Bayes
(Slides: PDF, PPTX — Video) |
Ch. 20.1-20.2.2 Note 9 |
Section 10 (video) (without solutions) |
HW10 Particle Filtering and Naive Bayes
[Electronic] [Written] (Due 4/22 11:59 pm) [Written solutions] |
|
4/17 Wed |
Machine Learning: Perceptrons
(Slides: PDF, PPTX — Video) |
Ch. 18.6.3 | ||||
13 | 4/22 Mon |
Machine Learning: Logistic Regression and Neural Networks
(Slides: PDF, PPTX — Video) |
Ch 18.8 | Section 11 (video) (without solutions) |
HW11 Perceptrons
[Electronic] [Written] (Due 4/29 11:59 pm) [Written solutions] |
|
4/24 Wed |
Machine Learning: Neural Networks and Decision Trees
(Slides: PDF, PPTX — Video) |
Ch 18.3 & 18.7 Note 10 |
||||
14 | 4/29 Mon |
Robotics / Language / Vision
(Slides: PDF — Video) |
N/A |
Final Review Bayes Networks (no soln ) Search (no soln ) Logic (no soln ) MDP/RL (no soln ) ML (no soln ) |
Practice ML Questions, solutions. |
P5 Classification
(Due 5/3 4 pm) |
5/1 Wed |
Advance Topics and Final Contest
(Slides: PDF, PPTX — Video) |
N/A | ||||
15 | 5/6 Mon | RRR Week | N/A | |||
5/8 Wed | RRR Week | |||||
16 | 5/13 Mon | Finals Week | N/A | |||
5/16 Thu | Final Exam (7 - 10 pm) (Final Prep) (Practice Final, no soln) |