Module 1

Topics: 

• Course Overview
• AI Overview
• Agent Architectures

Readings and Video Lessons

• Course Syllabus
• Overview AI
• Some videos
• Class recording

• Read Preface of ArtInt (4 pages) and read Chapter 1, through section 1.10 of ArtInt (about 44 pages) — est. 3 hours
• Read Chapter 2 through section 2.3 of ArtInt (15 pages) — est. 1 hour
• Robot Dreams and Cognitive Architectures (Lecture)

Assignments and Quizzes

• Assignment A-M1 online — est. 1.5 hours
• Programming Assignment P-M1
• Quiz Q-M1 online

Module 2

Topics:

• Uniformed Search
  

Readings and Video Lessons

• Read Chapter 3 through section 3.5.2 of ArtInt (20 pages) and watch Doug’s iterative deepening search video playlist (material from section 3.5.3 optional reading)  — est. 2 hours (bullet points 1 and 2 are all that you need do for quiz Q-w2)
• Watch further Uninformed Search video lecture, summary of basic search strategies, including cycle checking (from section 3.7.1 optional reading), multiple path pruning (from section 3.7.2 optional reading).
  • (and section 3.5.3 optional reading)

• Top Hat attendance
• Lecture (slides only) on uninformed search (because video was posted late)
• Discussion on uninformed search scenarios

• Post Week 2 Discussion Forum post on Brightspace by Tuesday, August 28, 11:59 PM. 
• Read Section 3.5.4 and  Section 3.6 (6 pages) of ArtInt and watch Doug’s blind/heuristic search video — est. 2 hours
• Lecture on heuristic search (playlist of two videos), including heuristic depth first search, best first search, A* search (from section 3.8.1 optional reading) (from section 3.8.2 optional reading)

Assignments and Quizzes:

• Assignment A-M2  — est. 1.5 hours
• Programming Assignment P-M2
• Quiz Q-M2

Module 3

Topics:

• Heuristic Search

Readings and Video Lessons

• Read Section 3.5.4 and  Section 3.6 (6 pages) of ArtInt and watch Doug’s blind/heuristic search video — est. 2 hours
• Lecture on heuristic search (playlist of two videos), including heuristic depth first search, best first search, A* search (from section 3.8.1 optional reading) (from section 3.8.2 optional reading)

• Additional comments on heuristic search (Slides only)

Assignments and Quizzes

• Assignment A-M3 — est. 1.5 hours
• Programming Assignment P-M3
• Quiz Q-M3

Module 4

Topics: 

• Planning under Certainty

Readings and Video Lessons

• Read Chapter 4, section 4.1 (6 pages) — est. 0.5 hour
• Read Chapter 5, section 5.1 (6 pages) — est. 0.5 hours
• Chapter 2, section 2.4 of ArtInt (7 pages) — est. 0.5 hours
  
• Read Chapter 6, through section 6.3 of ArtInt (15 pages) — est. 1.5 hour
• Watch feature-based planning under certainty pre-class lecture at ( https://www.youtube.com/playlist?list=PLXAjOiPf89kPlMXrJJEx2UjDci0_-hnUD ) (slides only)

• InClass lecture on course scheduling example
• Open discussion on propositional planning with certainty scenarios

• Post Week 3 Discussion Forum post on Brightspace by Tuesday, September 4, 11:59 PM. 
• Watch the A-w2 key video (slides only), which includes additional search material

• In-class presentation on propositional planning with certainty scenarios (slides only)

Assignments and Quizzes

• Assignment A-M4  — est. 1.5 hour
• Programming Assignment P-M4
• Quiz Q-M4

Module 5

Module Topics: 

• Constraint-satisfaction
• Optimization

Readings and Video Lessons

• Read Chapter 4, through section 4.3 (8 pages), first two pages of 4.5 (10 pages total)– est. 1 hr
• Watch Doug’s GAC video (section 4.4 optional reading) — est. 0.5 hr
• Watch pre-class lectures on Constraints, including more on GAC and Variable Elimination (sections 4.4 and 4.6 optional readings) — est. 1 hr
• Take online quiz Q-w4 by 8:00 am September 11

• Additional comments on constraint and optimization (slides only)

To Do before Thursday, September 13 class:

• Post Week 4 Discussion Forum post on Brightspace by Tuesday, September 11, 11:59 PM. 
• Read section 4.9 (7 pages) — est. 1 hour

• Real world constraint and optimization scenarios (slides only)
• Key for A-w3 (in the final side of the presentation there is a reference to a typo in the text. This has been corrected in the online version of the book). (slides only, corrected)

To Do After Thursday, September 13 class:

• Assignment A-M5 — est. 3 hours
• Programming Assignment P-M5
• Quiz Q-M5

Module 6

Week’s Topics: 

• Propositional inference and theorem proving

Readings and Video Lessons

• Read Chapter 5, through section 5.4 (27 pages), though section 5.1 should be review — est. 2 hours 
• Pre-class lecture on propositional logic basics and proof, including resolution proof by contradiction — est. 1.5 hours

• Retrospective (and study outline) before Exam 1 (slides only)

• Post Week 5 Discussion Forum post on Brightspace by Tuesday, September 18, 11:59 PM.
  

• Applications of theorem proving (slides only)

Assignments and Quizzes

• Assignment A-M6  — est. 2 hours 
• Programming Assignment P-M6
• Quiz Q-M6

Module 7

Topics: 

• Adversarial Search
  

Readings and Video Lessons

• Watch Pre-class lecture on Adversarial Search in Games (slides only) (Sections 11.1 – 11.3 of ArtInt, optional reading) — est. 1.5 hours
• Take online quiz Q-w6 by 8:00 am September 25

• More thoughts on Games and RadioLab The rules will set you free

• No Discussion Forum Post
• Study for Exam 1 — est. 4 hours (assuming that you have stayed up on material)

Assignments and Quizzes

• Assignment A-M7
  
• Programming Assignment P-M7
• Quiz Q-M7

Module 8

Topics: 

• Machine Learning

Readings and Video Lessons

• Read Section 8.1 on Probability basics as needed (13 pages) — material from 8.1 will NOT be on this week’s quiz, but may be required by some for lectures
  
• Read Chapter 7, sections 7.1 through 7.2,  (16 pages) — est. 2 hours
• Watch pre-class lecture on machine learning with decision trees (slides only) and evaluation of supervised machine learning systems (slides only). (optional reading of Section 7.3.1 and Sections 7.4 up to but not including 7.4.1, and section 7.4.3) — est. 2 hours
• Optional (this week) Watch an additional playlist on learning with Naive Bayesian Classifiers (slides only). It will be required in a subsequent week, but NBCs are not on this week’s quiz)
• In class quiz this week

• More machine learning fun

• Post Week 7 Discussion Forum post on Brightspace by Tuesday, September 18, 11:59 PM. 

• Applications of Machine Learning

Assignments and Quizzes

• Assignment A-M8 — est. 2.5 hours
• Programming Assignment P-M8
• Quiz Q-M8

Module 9

Topics: 

• Uncertainty (Probability and belief networks)

Readings and Video Lessons

• Read Chapter 8, sections 8.1 through 8.3 of ArtInt  — est. 1.5 hours
• Watch Pre-class lectures on uncertainty (first three videos of entire playlist, but see below) — est. 1 hour
  • Pre-class lectures on Probability Basics as needed (accompanies Chapter 8, through 8.1.2). Read through 8.1.2 and/or watch video if you haven’t been previously introduced to probabilities, or want a refresher)
  • Pre-class lecture on expected values and utilities (accompanies section 8.1.4) — this material will already be familiar to some, but applications in video probably won’t be (slides only)
  • Pre-class lecture on Bayes Rule, chain rule, and independence (accompanies 8.1.3 and 8.2)
• Watch Pre-class lecture playlist on learning with Naive Bayesian Classifiers (slides only). (this was an optional video in an earlier week; parts of this playlist repeat other videos for this week, so you might skip past these parts) — est. 1 hour
• Take online quiz Q-w8 by 8:00 am October 9

• Watch Pre-class lectures on uncertainty (videos 4, 5, and 6 of entire playlist) — est 2 hrs
  • Do both reading and lecture: Pre-class lecture on belief network semantics and construction (accompanying 8.3)
  • Do both reading and lecture: Pre-class lecture on belief network structure and semantics  (accompanying 8.3) (slides only)
  • Short video that preps for A-w8

• Belief Network exercises

Assignments and Quizzes

• Assignment A-M9 (This is formatted as a quiz on Brightspace with two submissions possible, and unlimited time per submission — all will be like this).
• Programming Assignment P-M9
• Quiz Q-M9

Module 10

Topics: 

• Inference with belief networks

Readings and Video Lessons

• Read Chapter 8, sections 8.1 through 8.3 of ArtInt  — est. 1.5 hours
• Watch Pre-class lecture inference with belief networks (slides only) (accompanies section 8.4, which is optional reading because video is all you need and somewhat deviates from the text) — est. 1 hour
  

• Belief networks

Assignments and Quizzes

• Assignment A-M10
• Programming Assignment P-M10
• Quiz Q-M10

Module 11

Topics: 

• Sequential Inference

Readings and Video Lessons

• Read Chapter 8, section 8.5 of ArtInt  —est. 2 hours — emphasis on 8.5.1, 8.5.2, and 8.5.6
• Watch Pre-class lectures on sequential inference with belief networks (first two videos of playlist) (slides only) —est. 1.5 hours —

• Post Week 10 Discussion Forum post on Brightspace by Tuesday, October 23, 11:59 PM.
  

• Markov Models and Hidden Markov Model Applications
• Heads up on student questions

Assignments and Quizzes

• Assignment A-M11
  
• Programming Assignment P-M11
• Quiz Q-M11

https://berkeleyai.github.io/cs188-website/index.html

Module 12

Topics: 

• Planning with uncertainty

Readings and Video Lessons

• Read Chapter 9, through Section 9.1 (13 pages) — est. 1.5 hours
• Watch Pre-class lectures on planning and decision making with uncertainty (third video of playlist) (slides only) —est. 1 hour

• Read Chapter 9, Section 9.2 through 9.3.2 (10 pages) — est. 1.5 hours

• Practice exam (will receive key after uploading answers as text file to Brightspace)

Assignments and Quizzes

• Assignment A-M-12
• Programming Assignment P-M12
• Quiz Q-M12

https://berkeleyai.github.io/cs188-website/index.html

Module 13

Topics:

• First Order Representations
  

Readings and Video Lessons

• Read  Chapter 13, sections 13.1-13.3 — est. 1.5 hours
• Pre-class lecture on lecture on first order representations (https://youtu.be/cOlsMSA41Ug) (slides only — a small corrected is made to fully parenthesize subexpressions to make operator precedence unambiguous)
• Read section 13.4 through 13.4.3 — est 1 hour
• Pre-class lecture on first-order representation, theorem proving, planning, and learning (https://www.youtube.com/playlist?list=PLXAjOiPf89kNFufXHt_A_y5zHLuMkYGuA )(slides only) — est. 1 hour

Assignments and Quizzes

• Submit Assignment A-w13 by Saturday, November 10 at 11:59 pm. — est. 1 hour
• Assignment for CS 5260 students only is posted
• Programming Assignment P-M13
• Quiz Q-M13

Module 14

Topics:

• Reinforcement Learning

Readings and Video Lessons

• Lightly read Sections 9.4, 9.5 (up to and not incl 9.5.1) and 12.1 — est 1 hour

• Guest lecture by Dr. Fernando Elliott on Reinforcement Learning (there will be no attendance taken, but there will be no Zoom recording of the session, and one or more questions from the lecture are guaranteed to be on the final exam). Dr. Elliott’s slides

• Guest lecture by Professor Maithilee Kunda on Machine Learning (there will be no attendance taken, but there will be no Zoom recording of the session, and one or more questions from the lecture are guaranteed to be on the final exam)

Assignments and Quizzes

• Assignment A-M14
• Programming Assignment P-M14
• Quiz Q-M14

Module 15

Topics:

• Special Topics
  • AI Story Telling
  • AI Sustainability
  • Integrative AI

Readings and Video Lessons

• Special Topics Lecture: AI Story Telling (slides)
• Submit Reading and Report for Graduate Credit
  
• Read (for final exam) “Interactive Narrative: An Intelligent Systems Approach” by Mark Owen Riedl, Vadim Bulitko  in AI Magazine, Vol. 34, No. 1, 2013 https://www.aaai.org/ojs/index.php/aimagazine/article/view/2449

• Read Section 16.2 on ethics and implications
• Wikipedia editing Wednesday, November 28 5:00 pm – 7:00 pm FGH 244 (guidelines)

• AI and Sustainability (slides)

Assignments and Quizzes

• Assignment A-M15
• Programming Assignment P-M15
• Quiz Q-M15

https://berkeleyai.github.io/cs188-website/index.html