Schedule - CSE 4308 - 001 and CSE 5360 - 001

Lecture videos are available on Blackboard.


L/no Date Chapters, 2nd Edition Chapters, 3rd Edition Topic
1 08/22 1, 2 1, 2 Course Details[1] and Overview[1], Agents[2]
2 08/27 3 3.1 - 3.4 Solving Problems by Search[2] (Contd.), Notes on Implementation[1]
3 08/29 4 3.5 - 3.6 Informed Search[2]
09/03 LABOR DAY - NO CLASS
4 09/05 6 5 Search (contd.), Game Playing[2]
5 09/10 6 5 Alpha - Beta Pruning[3], Non - Deterministic Games
6 09/12 5 6
 Constraint Satisfaction Problems[2]
7 09/17 7 7 Knowledge and Logic Reasoning[2]
8 09/19 Exam 1 Review
09/24 EXAM 1
9 09/26 7 7 Exam 1 Discussion, Inference by Enumeration
10 10/01 7 7 Forward and Backward Chaining, Resolution
11 10/03 8.1-8.3, 9.1.2, 9.2 8.1-8.3, 9.1.2, 9.2 First Order Logic[3], Unification & FC/BC[2]
12 10/08 11 10 Planning[3], Planning[2]
13 10/10 12 11 Conditional Planning and Replanning[3], Conditional Planning and Replanning[2]
13 10/15 13 13 Probablity[2]
14 10/17 13 13 Joint Probablity Distribution
15 10/22 13 13 Prior and Posterior Probablites[3]
16 10/24 Exan 2 Review
10/29 EXAM 2
17 10/31 14.1 - 14.4 14.1 - 14.4 Exam 2 Discussion, Bayesian Networks[3], Bayesian Networks[2]
18 11/05 14.1 - 14.4 14.1 -14.4 Bayesian Networks (Contd.)
19 11/07 18.1-18.3 18.1-18.3 Learning[3], Learning[2]
20 11/12 18.1-18.3 18.1-18.3 Decision Trees[3]
21 11/14 18.1-18.3 18.1-18.3 Practical Issues with Decision Trees[3]
22 11/19 20.3 Bayesian Classifiers[3]
11/21 THANKSGIVING HOLIDAY - NO CLASS
24 11/26  18.8.1Probabilty Estimations, Nearest Neighbor Classifiers[3]
25 11/28 20.518.6.4, 18.7Neural Networks[2], Neuron Architeture[1][4],  Backpropogation Learning[3]
26 12/03 20.518.6.4, 18.7 Backpropogation Learning, Introduction to Deep Learning
27 12/05 Exam 3 Review, Final Q & A
12/07 EXAM 3 - CSE 5360
12/12 EXAM 3 - CSE 4308


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)