COMP 372: Artificial Intelligence, Spring 2017

Administrivia

Resources

Schedule

Date Topic Required Reading Notes Assignments Out Slides
1/12 Introduction, agents chaps 1 and 2 slides
1/17 State space search, uninformed search 3.1-3.4 Project 0, due on Moodle on 1/24, 11:55pm slides
1/19 Heuristic search, A* 3.5 (see previous slides)
1/24 Finish heuristic search 3.6 slides
1/26 Adversarial search: minimax 5.1-5.2 Project 1, due on Moodle on Thu 2/9, 11:55pm
Homework 1, due at the start of class on Tue 2/7
slides
1/31 Adversarial search: alpha-beta pruning 5.3 (see previous slides)
2/2 Adversarial search: heuristic evaluation functions 5.4-5.5 slides
2/7 Probability I 13.1-13.3 (no slides)
2/9 Probability II 13.4-13.5 (no slides)
2/14 Bayes Nets I 14.1-14.2 (no slides)
2/16 Bayes Nets II (exact inference) 14.3 (no slides)
2/21 Bayes Nets III (approximate inference) 14.4 Project 2, due on Moodle on Fri 3/3, 5:00pm
slides
2/23 Statistical inference: ML & MAP Homework 2, due at the start of class on Tue 3/14 slides
2/28 Statistical inference: Combining evidence slides
3/2 Statistical inference: Naive bayes classifiers slides
3/7 Spring break
3/9 Spring break
3/14 Markov chains all Markov slides
3/16 Hidden Markov models
3/21 Midterm
3/23 Hidden Markov models, continued Project 3, due on Moodle on Thu 4/6, 11:55pm
3/28 Reinforcement learning I all RL slides
3/30 Reinforcement learning II Homework 3, due at the start of class on Tue 4/11
4/4 Reinforcement learning III
4/6 Reinforcement learning IV
4/11 Reinforcement learning practice Project 4, due on Moodle on Thu 4/25, 11:55pm
4/13 Easter break
4/18 Neural networks I all NN slides
4/20 Neural networks II
4/25 Neural networks III lab
4/27 Wrapup wrapup slides