Learning Objective

There are three primary objectives for the course:

The course is designed to present a solid entry point to the field of artificial intelligence. It will provide the foundation to go on to take other upper division AI courses. For those students with interest, it could possibly lead to subsequent research opportunities.

Course Content

There is no generally accepted definition of artificial intelligence. Some that have been proposed include:

This course provides a broad introduction to artificial intelligence. Topics include:

Schedule

Week / Date Lectures Homework Projects
Week 1
Aug 24 2022
Introduction to AI HW0 PJ0
Week 2
Aug 31 2022
Search HW1 PJ1
Week 3
Sep 7 2022
Constraint Satisfaction Problems HW2
Week 4
Sep 14 2022
Adversarial Search HW3 PJ2
Week 5
Sep 21 2022
Markov Decision Processes HW4
Week 6
Sep 28 2022
Reinforcement Learning HW5 PJ3
Week 7
Oct 5 2022
Probability and Bayes Nets: Representation
Week 8
Oct 12 2022
Bayesian Networks: Inference HW6
Week 9
Oct 19 2022
Bayesian Networks: Independence and Sampling HW7 PJ4
Week 10
Oct 26 2022
Decision Networks, VPI, and Hidden Markov Models HW8
Week 11
Nov 2 2022
Particle filtering and Machine Learning: Naïve Bayes
Week 12
Nov 9 2022
Machine Learning: Perceptrons and Logistic Regression HW9
Week 13
Nov 16 2022
Machine Learning: Optimization and Neural Networks HW10 PR5
Week 14
Nov 23 2022
Thanks Giving No Classes
Week 15
Nov 30 2022
Advanced Applications: Games and Robotics and Conclusion
Week 16
Dec 7-14 2022
Exams