L/no	Date	Chapters, 2nd Edition	Chapters, 3rd Edition	Chapters, 4th Edition	Topic
1	08/22	1	1	1	Course Details[1] and Overview[1]
2	08/24	2, 3	2, 3.1 - 3.4	2, 3.1 - 3.4	Agents[2], Solving Problems by Search[2]
3	08/29	4	3.5 - 3.6	3.5 - 3.6	Informed Search[2]
4	08/31	4	3.5 - 3.6	3.5 - 3.6	Search (contd.), Notes on Implementation[1]
	09/05				LABOR DAY - NO CLASS
	09/07				QUIZ 1
5	09/12	6	5	5	Game Playing[2], Alpha - Beta Pruning[3]
6	09/14	6, 5	5, 6	5, 6	Non - Deterministic Games, Constraint Satisfaction Problems[2]
7	09/19	5	6	6	CSP (contd.)
8	09/21	7	7	7	Knowledge and Logic Reasoning[2], Inference by Enumeration
9	09/26	7	7	7	Forward and Backward Chaining, Resolution
	09/28				QUIZ 2
10	10/03	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	10/05	11	10	11	Planning[3], Planning[2]
12	10/10	12	11	11	Conditional Planning and Replanning[3], Conditional Planning and Replanning[2]
13	10/12	13	13	12	Probablity[2]
14	10/17	13	13	12	Joint Probablity Distribution, Prior and Posterior Probablites[3]
	10/19				QUIZ 3
15	10/24	14.1 - 14.4	14.1 - 14.4	13.1-13.4	Bayesian Networks[3], Bayesian Networks[2]
16	10/26	14.1 - 14.4	14.1 - 14.4	13.1-13.4	Bayesian Networks (Contd.)
17	10/31	18.1-18.3	18.1-18.3	19.1-19.3	Learning[3], Learning[2]
18	11/02	18.1-18.3	18.1-18.3	19.1-19.3	Decision Trees[3]
19	11/07	18.1-18.3	18.1-18.3	19.1-19.3	Practical Issues with Decision Trees[3]
	11/09				QUIZ 4
20	11/14		20.3	20.3	Bayesian Classifiers[3]
21	11/16		20.3	20.3	Probabilty Estimations
22	11/21		18.8.1	19.7.1	Nearest Neighbor Classifiers[3]
	11/23				THANKSGIVING HOLIDAY - NO CLASS
23	11/28	20.5	18.6.4, 18.7	19.6.4, 21.1	Neural Networks[2], Neuron Architeture[1][4],  Backpropogation Learning[3]
	11/30				QUIZ 5
	12/05				Final Exam Review Session, Final Q & A
	12/07				STUDENT STUDY DAY - NO CLASS
	12/12				FINAL EXAM - Check here for exact Date and Time
	12/14				FINAL EXAM - Check here for exact Date and Time

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)