Computer Science 242

Artifical Intelligence

Fall 2025

Instructor: Ted Pawlicki office hours on instructor website.

TAs:

  • Yolo Tang ytang37@UR.rochester.edu
  • Pai Liu pliu29@UR.rochester.edu
  • Junjie Zhao jzhao58@u.rochester.edu

Location: Tu/Th 3:25pm-4:40pm, Wegmans 1400

Prereqs: Data structures and algorithms.

Homework Projects

Required text: Stuart Russell and Peter Norvig, Artificial Intelligence, A Modern Approach, 4th ed. (2020).

If you want to add the class, complete the first project, and then email it to pawlicki@cs along with a note including your year and major.

Syllabus

DateTopicReading
8/26 Problem Solving 3.0-3.3.3
8/28 Search Strategies 3.3.4-3.6.1
9/2 Adversarial Search 5.0-5.2.1
9/4 Adversarial Search 2 5.3-5.3.2; 5.5-5.6; 5.7
9/9 Local Search 4.0-4.1
9/11 Local Search 2 4.3-4.4; 4.2, 4.5
9/16 Midterm 1
9/18 midterm solutions
9/23 Constraint Satisfaction 6.0-6.5
9/25 Propositional Logic 7.0-7.4
10/30 Propositional Theorem Proving 7.5
10/2 First Order Logic 8.0-8.3
10/7 First Order Theorem Proving 9
10/9 Midterm 2
10/14 no class
10/16 midterm solutions
10/21 Representing Uncertainty 12.0-12.2; 12.2.3
10/23 Uncertain Inference 12.3-12.7
10/27 Bayesian Networks 13.0-13.2.1; 13.3-.3
10/30 Approximate Inference in Bayesian Networks 13.4; 13.5
11/4 Inference in Temporal Models 14.0-14.2; 14.3
11/6 review / problem solving
11/11 Learning From Examples, Decision Trees 19.0-19.3, 19.4.0
11/13 Linear Regression and Linear Classifiers 19.6, logistic regression
11/18 Neural networks 21.0-21.2, 21.4, 21.5.3, 21.6.1, 24.4.1
11/20 Learning Probabilistic Models 20.0-20.2.2; 20.2.7
11/25 Learning with Incomplete Data 20.3.0, 20.3.4
11/27 no class
12/2 review / problem solving
12/4 Review
Final Exam: Monday, December 15, 8:30am-11:30am, 1400 Wegmans.

Grading

  • Homeworks: 40%
  • Midterms: 25%
  • Final: 35%

pawlicki @ cs rochester edu
August 19, 2025