Schedule - CSE 4308 - 001, CSE 4308 - 003, CSE 5360 - 001 and CSE 5360 - 001

Lecture videos are available on Canvas.


L/no Date Chapters, 2nd Edition Chapters, 3rd Edition Topic
1 08/21 1, 2 1, 2 Course Details[1] and Overview[1], Agents[2]
2 08/26 3 3.1 - 3.4 Solving Problems by Search[2] (Contd.), Notes on Implementation[1]
3 08/28 4 3.5 - 3.6 Informed Search[2]

09/02

LABOR DAY - NO CLASS
4 09/04 6 5 Search (contd.), Game Playing[2]
5 09/09 6 5 Alpha - Beta Pruning[3], Non - Deterministic Games
6 09/11 5 6
 Constraint Satisfaction Problems[2]
7 09/16 7 7 Knowledge and Logic Reasoning[2]
8 09/18

Exam 1 Review

09/23

EXAM 1
9 09/25 7 7 Exam 1 Discussion, Inference by Enumeration
10 09/30 7 7 Forward and Backward Chaining, Resolution
11 10/02 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 10/07 11 10 Planning[3], Planning[2]
13 10/09 12 11 Conditional Planning and Replanning[3], Conditional Planning and Replanning[2]
13 10/14 13 13 Probablity[2]
14 10/16 13 13 Joint Probablity Distribution
15 10/21 13 13 Prior and Posterior Probablites[3]
16 10/23

Exan 2 Review

10/28

EXAM 2
17 10/30 14.1 - 14.4 14.1 - 14.4 Exam 2 Discussion, Bayesian Networks[3], Bayesian Networks[2]
18 11/04 14.1 - 14.4 14.1 -14.4 Bayesian Networks (Contd.)
19 11/06 18.1-18.3 18.1-18.3 Learning[3], Learning[2]
20 11/11 18.1-18.3 18.1-18.3 Decision Trees[3]
21 11/13 18.1-18.3 18.1-18.3 Practical Issues with Decision Trees[3]
22 11/18
20.3 Bayesian Classifiers[3]
24
 11/20
 18.8.1 Probabilty Estimations, Nearest Neighbor Classifiers[3]
25
 11/25 20.518.6.4, 18.7Neural Networks[2], Neuron Architeture[1][4],  Backpropogation Learning[3]

11/27

THANKSGIVING HOLIDAY - NO CLASS
26 12/02 20.518.6.4, 18.7 Backpropogation Learning, Introduction to Deep Learning
27 12/04

Exam 3 Review, Final Q & A

12/09

EXAM 3 - CSE 4308 003, CSE 5360 001, CSE 5360 003

12/11

EXAM 3 - CSE 4308 001


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)