Lecture videos are available on Blackboard.

L/no Date Chapters, 2nd Edition Chapters, 3rd Edition Topic
1 Mon 08/28 1, 3 1, 3.1 - 3.4 Course Details[1] and Overview[1], Solving Problems by Search[2]
2 Wed 08/30 1, 3 1, 3.1 - 3.4 Solving Problems by Search[2] (Contd.), Notes on Implementation[1]
3 Wed 09/06 4 3.5 - 3.6 Informed Search[2]
4 Mon 09/11 2, 6 2, 5 Agents[2], Game Playing[2]
5 Wed 09/13 6 5 Game Playing (Contd.)
6 Mon 09/18 6 5 Alpha - Beta Pruning[3], Non - Deterministic Games
7 Wed 09/20 7 7 Knowledge and Logic Reasoning[2]
8 Mon 09/25 7 7 Inference by Enumeration, Exam 1 Review
Wed 09/27 EXAM 1
9 Mon 10/02 7 7 Exam 1 Discussion, Forward and Backward Chaining
10 Wed 10/04 7, 8.1-8.3, 9.1.2 7, 8.1-8.3, 9.1.2 Resolution, First Order Logic[3]
11 Mon 10/09 8.1-8.3, 9.1.2 8.1-8.3, 9.1.2 First Order Logic (Contd.)
12 Wed 10/11 11 10 Planning[3], Planning[2]
13 Mon 10/16 12 11 Conditional Planning and Replanning[3], Conditional Planning and Replanning[2]
13 Wed 10/18 9.2 9.2
 First Order Logic Revisit - Unification & FC/BC[2]
14 Mon 10/23 13 13 Probablity[2]
15 Wed 10/25 13 13 Joint Probablity Distribution
16 Mon 10/30 13 13 Exam 2 Review, Prior and Posterior Probablites[3]
Wed 11/01 EXAM 2
17 Mon 11/06 13 13 Prior and Posterior Probablites
18 Wed 11/08 14.1 - 14.4 14.1 - 14.4 Bayesian Networks[3], Bayesian Networks[2]
19 Mon 11/13 18.1-18.3 18.1-18.3 Learning[3], Learning[2]
20 Wed 11/15 18.1-18.3 18.1-18.3 Decision Trees[3]
21 Mon 11/20 18.1-18.3 18.1-18.3 Practical Issues with Decision Trees[3]
22 Wed 11/22 20.3, 18.8.1 Bayesian Classifiers[3], Nearest Neighbor Classifiers[3]
23 Mon 11/27 20.5 18.6.4, 18.7 Neural Networks[2], Neuron Architeture[1][4],  Backpropogation Learning[3]
24 Wed 11/29 20.5 18.6.4, 18.7 Exam 3 Review, Backpropogation Learning
Mon 12/04 EXAM 3
25 Wed 12/06 Exam 3 Discussion, Optional  Assignment Information, Final Q & A
Wed 12/13 OPTIONAL EXAM (CSE 5360) 2:00 PM - 3:30 PM
Fri 12/15 OPTIONAL EXAM (CSE 4308) 2:00 PM - 3:30 PM
Fri 12/15 OPTIONAL ASSIGNMENT DUE


This schedule is tentative and subject to change. If changes are necessary they will be announced in class and posted here.
[1] (c) Vamsikrishna Gopikrishna, University of Texas at Arlington.
[2] (c) Stuart Russell (Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig. ISBN: 978-0136042594)
[3] (c) Vassilis Athitsos, University of Texas at Arlington.
[4] (c) Martin Hagan (Neural Network Design. Martin T. Hagan, Howard B. Demuth, Mark H. Beale. ISBN: 0-9717321-0-8)