Artificial Intelligence: CSC 242
Perpetually-updated Syllabus and Schedule

"Sometimes I wish Newt would take some lessons, so he could know for sure if he was doing something or not," [Newt's sister says].
"Self-taught, are you?" Julian Castle asked Newt.
"Isn't everybody?" Newt inquired.
"Very good answer." Castle was respectful.

-- Kurt Vonnegut, Cat's Cradle .

Procrastination is the grave in which opportunity is buried.

--- Dennis Kimbro.

Any fool can drown; that's the easy bit.

--- Pete Goss, solo sailor

RN = Russell and Norvig

The Reading listed for a day should be done BEFORE that day. Don't forget that Berkeley overheads and more goodies are available at The AIMA Website . You have to go to the "information for instructors".

The syllabus may well be updated as reality intrudes, so be prepared for variations.

Written assignments due in instructor's hands or in-box outside CSB735 by 5pm on indicated day.

Programming Projects due 11:55 Sunday near indicated date; see Blackboard for authoritative dates and times.

Lec Date Subject Reading Ass't Lecture Ex. Ass't Ex. Due
1 R 1.14 AI Overview RN 1 (all), Quagents, Quagent Tech Report, Radiant Editor Tutorial. aima EX1 None
2 T 1.19 Agents RN 2 (all) aima 3-D Tictactoe None
3 R 1.21 Problem Solving RN 3, CBNotes , N-Jug Code , aima none none
4 T 1.26 Prob Solving, Search, Games RN 3 (all), RN 6 none EX2 EX1
5 R 1.28 Heuristic Search, Games RN 4 (all) aima, CBNotes none none
6 T 2.2 Search and Games cont. nothing new aima none none
7 R 2.4 CSPs RN 5 (all) aima Production Sys. 3DTTT
8 T 2.9 Production Systems Quickie Jess PPT , also Jess Intro aima none none
9 R 2.11 Knowledge Rep. RN 8 (all) aima EX3 EX2
10 T 2.16 Logic: CNF, Resolution RN 7.1, .3-.5, .8, RN9 -pp306-309. aima none none
11 R 2.18 Unification RN 9 -pp306-309, 10 (optional) aima none none
12 T 2.23 NLU RN 22 (22.7, .8 optional) aima EX4 EX 3
13 R 2.25 NLU cont. RN 22, 23 (optional) aima Quagent NLU JESS Prod. Syst.
14 T 3.2 Planning RN 11.1-11.4 aima none none
15 R 3.4 Midterm None none none
16 T 3.9 Spring Recess 1 None None none none
17 R 3.11 Spring Recess 2 None None None none
18 T 3.16 Planning cont. RN 11.1-11.4, 12 (opt.) aima None EX5 EX4
19 R 3.18 Probability RN 13 aima None none
20 T 3.23 Prob. cont. RN 13,14 aima Term Project Proposal none
21 R 3.25 Prob. III RN 14 aima Quagent Learning NLU
22 T 3.30 Learning RN 17.1-17.3 aima EX6 EX5
23 R 4.1 Learning II RN 21 aima none none
24 T 4.6 Utilities RN 16 aima none Term Project Proposal
25 R 4.8 Neu. Nets, Classif. RN 20.5-20.7, 24 Class. Notes aima EX7 , --
26 T 4.13 Vision I: Lin. Syst. RN 24 aima none E6
27 R 4.15 Vis. & Structure Matching None None Vision or Term Proj Learning
28 T 4.20 Linear Systems None None none none
29 R 4.22 3-D inference or robotics robots: RN 25 (can skip 25.3) aima None EX7
30 T 4.27 2nd midterm all since 1st midterm aima none none

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Last update: 12.30.05