Chapters 2, 3, 4 through 4.3 page 115 (simulated annealing), 5 through 5.2 page 145 (arc consistency), Chapter 7 through 7.5, Chapter 8 through 8.2, Chapter 9 (9.1, 9.2 through page 277, 9.3,  9.5 through page 300.

681 (graduate students) are also responsible for Chapter 6, especially minimax and alpha-beta pruning.

Midterm Exam from Fall 2001 (PDF)

Knowledge of our earlier material is essential to understanding this material, so you still need to know search methods, environmental/agent characteristics, and knowledge representation techniques.

Chapters 11 (planning), 13, 14 through pg 507 (bayes nets), 17-17.3 (MDPs), 18-18.4(decision trees, ensembles), 20 through pg 718 (simple amaximum likelihood learning), 20.5 (neural nets), 21-21.2(passive reinforcement learning)

FINAL Exam from Fall 2001 (PDF)

Problem 17.4 in book (MDP practice from HW #6)

Solution

Another MDP/RL problem from 2004 exam

   ...and the solution.

Problem 20.11 (NN practice from HW#6)

Solution