Course Topics

Please go to eCommons for detailed Course Schedule.

The general outline and order of topics is as follows:

M0: Introduction, R&N ch 1

M1: Heuristic Search, R&N ch 3.1-3.6

M2: Constraint Satisfaction, ch 6.1, 6.3-6.5

M3: Adversarial Search and Game Playing, ch. 5, 16.1-3

M4: Markov Decision Processes & Reinforcement Learning, Sutton and Barto Ch. 3 - 4, Ch. 17.1 - 3, Sutton and Barto Ch. 6.1, 2, 5

M5: Knowledge Representation and Theorem Proving, ch 7, 8 and 9

M6: Bayesian Networks, ch 13.1-5, 14.1-2, 4, 14.3

M7, M8: Machine Learning 1&2, ch18.1-3, 20.1-20.2.4, 18.6.3, 18.7-18.8