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Spring 2018 Syllabus

This syllabus is subject to change! Note that unreleased project out and due dates are just guesses and will likely change somewhat.

Note: To view the videos, login with @berkeley.edu credentials.

Day Topic Optional Reading Slides and Notes

Video
(see note above)

Assignment Due
Wed 1/17 Introduction to AI Ch. 1,
Ch. 2

[pptx]
[pdf]

video Math Self-Diagnostic
P0: Tutorial
(ungraded)
Fri 1/26 11:59pm

Mon 1/22 Agents and Search Ch. 3.1-4

[pptx]
[pdf]

lecture notes 1

discussion 1

solutions + video

video

Wed 1/24 A* Search and Heuristics Ch. 3.5-6

[pptx]
[pdf]

video

HW1

P1: Search
Contest 1: Search

W 1/31 11:59pm

M 2/5 11:59pm
TBD


Mon 1/29 Constraint Satisfaction Problems Ch. 6.1

[pptx]
[pdf]

lecture notes 2

video

Wed 1/31 CSPs II Ch. 6.2-5,
Ch. 4.1 

[pptx]
[pdf]

lecture notes 2

[discussion]
[discussion solution]

[exam prep]
[exam prep solution]

video HW2 W 2/7 11:59pm

Mon 2/5 Game Trees: Minimax Ch. 5.1-3

[pdf]
[pptx]

lecture notes 3

video

Wed 2/7 Game Trees: Expectimax; Utilities Ch. 5.4-5

[pdf]
[pptx]

lecture notes 3

[discussion]

[discussion solutions]


[exam prep]

[exam prep solutions]

video

HW3

P2: Multi-Agent Search

W 2/14

M 2/19


Mon 2/12 Markov Decision Processes

Ch. 16.1-3,
Ch. 17.1-2

[pdf]
[pptx]

lecture notes 4

video
Wed 2/14 Markov Decision Processes II Ch. 17.3

[pdf]
[pptx]

[exam prep]
[solutions]

[discussion]
[solutions]

lecture notes 4

video HW4 W 2/21 11:59pm

Mon 2/19 Holiday

PDF

lecture notes 5

Wed 2/21

Reinforcement Learning

Ch. 21.1-3

PDF

lecture notes 5

video

HW5

P3: Reinforcement Learning

W 2/28 11:59pm

M 3/5 11:59pm


Mon 2/26

Reinforcement Learning II

Ch. 21.4-5

PDF

video
Wed 2/28 RL/Probability/Bayes
Ch. 13.1-5 (2e: Ch. 13.1-6)

PDF

lecture notes 6

video

Mon 3/5 RL/Bayes Nets  Ch. 14.1-2,4 

PDF

lecture notes 6

video

HW6

M 3/12 11:59pm

Wed 3/7 Bayes' Nets: Representation/Independence Ch. 14.3, Jordan 2.1

PDF

lecture notes 6

video


Mon 3/12 Bayes' Nets: Independence/Inference Ch. 14.4-5

PDF

video
Wed 3/14

Midterm (xx-xx)

P4: Bayes Nets M 4/2 11:59pm

Mon 3/19

Bayes' Nets: Inference/Sampling

Ch. 15.1-3, 6

PDF

lecture notes 7

video
Wed 3/21

Bayes' Nets:  Sampling/Decision Networks

Ch. 15.2-5

PDF

lecture notes 8

video HW7 W 4/4 11:59pm

Mon 3/26

Spring Break!

Ch. 15.2,6

Wed 3/28

Spring Break!!

Ch. 15.2,6


Mon 4/2

Decision Networks/VPI

Ch. 15.2,6

PDF

lecture notes 10

video
Wed 4/4 Markov Models, HMMs video

HW8

P5: Ghostbusters

W 4/11 11:59pm

M 4/16 11:59pm


Mon 4/9

HMMs/Particle Filtering

Ch. 15.2,6

PDF

video
Wed 4/11 ML:Naive Bayes. Ch. 15.2,6 PDF video

Mon 4/16

ML: Perceptrons

Ch. 15.2,6 PDF video P6: Machine Learning see piazza
Wed 4/18 ML: Deep Learning Ch. 15.2,6 PDF video

Mon 4/23 Special Topics

PDF

video
Wed 4/25 Special Topics PDF video
Fri 5/11 FINAL EXAM (3:00pm-6:00pm)