CS 4700/5700: Foundations of Artificial Intelligence

Enrollment Questions

Most questions about enrollment are not specific to this course and you'll find the answers at:

If, after reading the above resources, you still have a question about getting into the course, please file a help ticket at https://tdx.cornell.edu/TDClient/193/Portal/Home/. Thank you!

Course Staff:

Course email

CS 4700/5700 online

Prerequisites:

Officially this course lists CS2110/ENGRD2110 and CS2800 as prerequisites. What follows is the more specific list of topics that the course will assume you know. If you don't know them yet, don't take the course hoping you'll pick them up along the way. There is ample evidence that students who do so struggle in the course. If you know the following, regardless of the courses taken, then that's all we care about. This is a senior/master's-level CS course, and we will expect that level of background from students.

Textbook:

Grading:

Grade components: Your final grade percentage will be computed from the following course elements in the percentages listed: Additional grading information:

Class Policies

Course Schedule

Starting Monday January 22, lectures will take place Mondays and Wednesdays 2:55pm - 4:10pm in Hollister Hall B14. The schedule of lectures and homeworks is as follows. (We may tweak this schedule as the semester progresses.) Slides for each lecture will be posted on Canvas just before the relevant lecture under Files > Slides.
Date Title Readings Homework
1/22 Overview
1/24 Uninformed Search Russell & Norvig Ch. 3.1-4 HW 1 out, due 2/5
1/29 Informed Search Russell & Norvig Ch. 3.5-6
1/31 Local search Russell & Norvig Ch. 4.1-2
2/5 Game Trees: Minimax Russell & Norvig Ch. 5.1-3 HW 1 due
HW 2 out, due 2/14
2/7 Game Trees: Expectimax, Utilities Russell & Norvig Ch. 5.5, 16.1-16.3
2/12 Markov Decision Processes 1 Russell & Norvig Ch. 17.1-3
2/14 Markov Decision Processes 2 Russell & Norvig Ch. 17.1-3 HW 2 due
HW 3 out, due 3/4
2/19 Reinforcement Learning 1 Russell & Norvig Ch. 21
2/21 Reinforcement Learning 2 Russell & Norvig Ch. 21
2/24-2/27 February Break
2/28 Bandits, Monte Carlo Tree Search
3/4 Probability Russell & Norvig Ch. 12.1-6 HW 3 due
3/6 Bayes Nets Russell & Norvig Ch. 13.1-2 HW 4 out, due 4/10
Masters (5700) HW out, due 3/25
3/11 Independence Russell & Norvig Ch. 13.1-2
3/13 Bayesian Inference and Prediction
3/14 Prelim Exam 7:30pm, location TBD
3/18 Exact Inference Russell & Norvig Ch. 13.3
3/20 Sampling Methods Russell & Norvig Ch. 13.4
3/25 Hidden Markov Models 1 Russell & Norvig Ch. 14.1-3 Masters (5700) HW due
3/27 Hidden Markov Models 2 Russell & Norvig Ch. 14.1-3
3/30-4/7 Spring Break
4/8 Decision Networks / VPI Russell & Norvig Ch. 16.5-6
4/10 Propositional Logic 1 Russell & Norvig Ch. 7.1-4 HW 4 due
HW 5 out, due 4/24
4/15 Propositional Logic 2 Russell & Norvig Ch. 7.5 - 7.7
4/17 First-Order Logic 1 Russell & Norvig Ch. 9.1-5
4/22 First-Order Logic 2 Russell & Norvig Ch. 9.1-5
4/24 Planning 1 Russell & Norvig Ch. 11.1-3 HW 5 due
HW 6 out, due 5/6
4/29 Planning 2 Russell & Norvig Ch. 26.5
5/1 Modern machine reasoning
5/6 Special Topics in AI HW 6 due
TBD, 5/13-5/20 Final Exam