CS 4700/5700: Foundations of Artificial Intelligence

(Last update: January 5, 2023)

Enrollment Questions

If you have a question about getting into the course, please contact the CS Enrollment Administrator at cs-course-enroll@cornell.edu. Most questions about enrollment are not specific to this course and you'll find the answers at:

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 (the "2%" will be explained in a moment): Additional grading information:

Class Policies

Course Schedule

Starting January 23, lectures will take place Mondays and Wednesdays 2:45pm - 4:00pm 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.

1/23

Overview

1/25

Uninformed Search

Russell & Norvig Ch. 3.1-4

1/25

Homework 1 out

Due 2/9

1/30

Informed Search

Russell & Norvig Ch. 3.5-6

2/1

Local search

Russell & Norvig Ch. 4.1-2

2/6

Game Trees: Minimax

Russell & Norvig Ch. 5.1-3

2/8

Game Trees: Expectimax, Utilities

Russell & Norvig Ch. 5.5, 16.1-16.3

2/8

Homework 2 out

Due 2/23

2/9

Homework 1 due

2/13

Markov Decision Processes 1

Russell & Norvig Ch. 17.1-3

2/15

Markov Decision Processes 2

Russell & Norvig Ch. 17.1-3

2/20

Reinforcement Learning 1

Russell & Norvig Ch. 21

2/22

Reinforcement Learning 2

Russell & Norvig Ch. 21

2/23

Homework 2 due

2/25-2/28

February Break

3/1

Probability

Russell & Norvig Ch. 12.1-6

3/1

Homework 3 out

Due 3/10

3/6

Bayes Nets

Russell & Norvig Ch. 13.1-2

3/8

Independence

Russell & Norvig Ch. 13.1-2

3/10

Homework 3 due

3/13

Exact Inference

Russell & Norvig Ch. 13.3

3/15

Sampling Methods

Russell & Norvig Ch. 13.4

3/16

Prelim Exam

7:30pm, location TBD

3/20

Hidden Markov Models 1

Russell & Norvig Ch. 14.1-3

3/20

Homework 4 out

Due 3/31

3/22

Hidden Markov Models 2

Russell & Norvig Ch. 14.1-3

3/27

Decision Networks / VPI

Russell & Norvig Ch. 16.5-6

3/29

Machine learning 1

Russell & Norvig Ch. 20.1-20.2.2

3/31

Homework 4 due

4/1-4/9

Spring Break

4/10

Machine learning 2

Russell & Norvig Ch. 18.6.3

4/10

Homework 5 out

Due 4/25

4/12

Machine learning 3

Russell & Norvig Ch. 18.8

4/17

Machine learning 4

4/19

Propositional Logic 1

Russell & Norvig Ch. 7.1-4

4/24

Propositional Logic 2

Russell & Norvig Ch. 7.5 - 7.7

4/24

Homework 6 out

Due 5/9

4/25

Homework 5 due

4/26

First-Order Logic

Russell & Norvig Ch. 9.1-5

5/1

Planning

Russell & Norvig Ch. 11.1-3

5/3

Special Topics in AI 1

5/8

Special Topics in AI 2

5/9

Homework 6 due

TBD, 5/13-5/20

Final Exam