Week 1: Introduction (1/19,21)

Week 2: Search (1/26,28):

Week 3: Beyond Classical Search (2/2,4):

Week 4: Adversarial Search (2/9,11)

Week 5: Probability (2/16,18)

Week 6: Utilities and MDPs (2/16,18)

Week 7: Reinforcement Learning (3/2,4)

Week 8: Midterm (3/9,11)

Week 9: Bayesian Networks (3/23,25):

Week 10: Probabilistic Reasoning over Time (3/30,4/1):

Week 11: Particle Filters (4/6,8):

Week 12: Learning Probabilistic Models (4/13,15):

Week 13: Supervised Learning (4/20,22):

Week 14: Classical Planning

Week 15: Philosophical Foundations

Final Exam