Date 
Topic 
Assignment 
Thu 8/17  Course overview and introduction.  Read recent
NY Times article on recent advances in AI 
Tues 8/22  Introduction to statespace search and uninformed search
algorithms: breadthfirst, uniformcost, depthfirst, and
iterativedeepening search Example: Cannibals and missionaries problem 
Read R&N textbook, chapter 3 
Thu 8/24  Introduction to informed (heuristic) search algorithms: A*, IDA*,
admissible and consistent heuristics Example: Slidingtile puzzle 
Helpful links for implementing A*: 0, 1, 2, 3 
Tues 8/29  Informed search algorithms continued: Branchandbound search Example: Traveling salesman problem 
Brief
review of depthfirst branchandbound search 
Thu 8/31  Constraintsatisfaction problems: backtracking search with
constraint propagation Examples: Sudoku, Nqueens, many others 
Read R&N textbook, chapter 6 Helpful links for implementing backtracking with constraint propagation: 0, 1 
Tues 9/5  Adversarial and gametree search Examples: Chess, checkers 
Read R&N textbook, chapter 5 
Thu 9/7  Quiz and review 

Tues 9/12  Local search, hill climbing, and related incomplete search
algorithms 
Read R&N textbook, sections 4.1 and 6.4 Local search for the traveling salesman problem 
Thu 9/14  Introduction to machine learning and neural networks 
1st programming assignment due 
Tues 9/19  Backpropagation algorithm for training feedforward multilayer neural networks  Read R&N textbook, section 18.7 Some helpful links for backpropagation: 1, 2, 3, 4, 5 
Thu 9/21  Learning decision trees  Read R&N textbook, sections 18.1 through 18.4 
Tues 9/27  Naive Bayes classifiers 
Readings on Naive Bayes classifiers: 1,
2 
Thu 9/29  Unsupervised learning and kmeans clustering 

Tues 10/3  Review for midterm  
Tues 10/10  Review for midterm 
2nd programming assignment due 
Thu 10/12  Midterm 

Tues 10/17  Markov decision processes: value iteration and policy iteration  Read R&N textbook, section 17.1, 17.2, 17.3 
Thu 10/19  Reinforcement learning: Qlearning  Read R&N textbook, chapter 21 
Tues 10/24  Reinforcement learning continued: SARSA learning 

Thu 10/26  Generalization in machine learning: biasvariance tradeoff 

Tues 10/31  Nearest neighbors classifiers 

Tues 11/7  3rd programming assignment due  
Thu 11/9  
Tues 11/14  
Thu 11/16  
Tues 11/21  
Tues 11/28  
Mon 12/4  Final exam 12  3 