L/no	Date	Chapters, 2nd Edition	Chapters, 3rd Edition	Chapters, 4th Edition	Topic
1	1/18	1	1	1	Course Details[1] and Overview[1]
2	1/20	2, 3	2, 3.1 - 3.4	2, 3.1 - 3.4	Agents[2], Solving Problems by Search[2]
3	1/25	4	3.5 - 3.6	3.5 - 3.6	Informed Search[2]
4	1/27	4	3.5 - 3.6	3.5 - 3.6	Search (contd.), Notes on Implementation[1]
5	2/01	6	5	5	Game Playing[2], Alpha - Beta Pruning[3]
6	2/03	6, 5	5, 6	5, 6	Non - Deterministic Games, Constraint Satisfaction Problems[2]
7	2/08	5	6	6	CSP (contd.)
8	2/10	7	7	7	Knowledge and Logic Reasoning[2], Inference by Enumeration
9	2/15	7	7	7	Forward and Backward Chaining, Resolution
	2/17				Exam 1 Review
	2/22				EXAM 1
10	2/24	8.1-8.3, 9.1, 9.2	8.1-8.3, 9.1, 9.2	8.1-8.3, 9.1, 9.2	First Order Logic[3], Unification & FC/BC[2]
11	3/01	11	10	11	Planning[3], Planning[2]
12	3/03	12	11	11	Conditional Planning and Replanning[3], Conditional Planning and Replanning[2]
13	3/08	13	13	12	Probablity[2]
14	3/10	13	13	12	Joint Probablity Distribution, Prior and Posterior Probablites[3]
	3/15				SPRING VACATION - NO CLASS
	3/17				SPRING VACATION - NO CLASS
15	3/22	13	13	12	Inference by Enumeration
16	3/24	14.1 - 14.4	14.1 - 14.4	13.1-13.4	Bayesian Networks[3], Bayesian Networks[2]
17	3/29	14.1 - 14.4	14.1 - 14.4	13.1-13.4	Bayesian Networks (Contd.)
	3/31				Exam 2 Review
	4/05				EXAM 2
18	4/07	18.1-18.3	18.1-18.3	19.1-19.3	Learning[3], Learning[2]
19	4/12	18.1-18.3	18.1-18.3	19.1-19.3	Decision Trees[3]
20	4/14	18.1-18.3	18.1-18.3	19.1-19.3	Practical Issues with Decision Trees[3]
21	4/19		20.3	20.3	Bayesian Classifiers[3]
22	4/21		20.3	20.3	Probabilty Estimations
23	4/26		18.8.1	19.7.1	Nearest Neighbor Classifiers[3]
24	4/28	20.5	18.6.4, 18.7	19.6.4, 21.1	Neural Networks[2], Neuron Architeture[1][4],  Backpropogation Learning[3]
	5/03				Exam 3 Review, Final Q & A
	5/05				EXAM 3 - CSE 4308/5360 003 (8:00 AM), CSE 5360 001 (2:00 PM)
	5/10				EXAM 3 - CSE 4308 001 (2:00 PM), CSE 4308/5360 002 (8:15 PM)

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)