Schedule - CSE 4308 - 002 and CSE 5360 - 002

Lecture videos are available on Blackboard.

L/no Date Chapters, 2nd Edition Chapters, 3rd Edition Topic
1 01/16 1, 3 1, 3.1 - 3.4 Course Details[1] and Overview[1], Solving Problems by Search[2]
2 01/18 1, 3 1, 3.1 - 3.4 Solving Problems by Search[2] (Contd.), Notes on Implementation[1]
3 01/23 4 3.5 - 3.6 Informed Search[2]
4 01/25 2, 6 2, 5 Agents[2], Game Playing[2]
5 01/30 6 5 Game Playing (Contd.)
6 02/01 6 5 Alpha - Beta Pruning[3], Non - Deterministic Games
7 02/06 5 6
 Constraint Satisfaction Problems[2]
8 02/08 5 6 Constraint Satisfaction Problems 
9 02/13 7 7 Exam 1 Review, Knowledge and Logic Reasoning[2]
02/15 EXAM 1
10 02/20 7 7 Exam 1 Discussion, Inference by Enumeration, FC/BC
11 02/22 7, 8.1-8.3, 9.1.2 7, 8.1-8.3, 9.1.2 FC/BC (Contd.), Resolution, First Order Logic[3]
12 02/27 8.1-8.3, 9.1.2, 9.2 8.1-8.3, 9.1.2, 9.2 First Order Logic (Contd.),(Addl Material: Unification & FC/BC[2])
13 03/01 11 10 Planning[3], Planning[2]
14 03/06 12 11 Conditional Planning and Replanning[3], Conditional Planning and Replanning[2]
15 03/08 13 13 Probablity[2]
03/13 SPRING BREAK
03/15 SPRING BREAK
16 03/20 13 13 Probablity[2]
03/22 13 13 Exam 2 Review, Joint Probablity Distribution
17 03/27 13 13 EXAM 2
18 03/29 13 13 Exam 2 Discussion, Prior and Posterior Probablites[3]
19 04/03 14.1 - 14.4 14.1 - 14.4 Bayesian Networks[3], Bayesian Networks[2]
20 04/05 18.1-18.3 18.1-18.3 Learning[3], Learning[2]
21 04/10 18.1-18.3 18.1-18.3 Decision Trees[3]
22 04/12 18.1-18.3 18.1-18.3 Practical Issues with Decision Trees[3]
23 04/17 20.3, 18.8.1 Bayesian Classifiers
24 04/19 20.3, 18.8.1 Nearest Neighbor Classifiers[3]
25 04/24 20.5 18.6.4, 18.7 Neural Networks[2], Neuron Architeture[1][4],  Backpropogation Learning[3]
26 04/26 20.5 18.6.4, 18.7 Exam 3 Review, Backpropogation Learning
05/01 EXAM 3
27 05/03 Exam 3 Discussion, Optional  Assignment Information, Final Q & A
05/08 FINALS WEEK
05/10 FINALS WEEK


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)