Tentative Schedule for Tuesday - Thursday Sections (changes, if any, posted at the end)

Lecture videos and Class discussion recordings will be available on Canvas.

L/no Date Chapters, 2nd Edition Chapters, 3rd Edition Chapters, 4th Edition Topic
1 08/18
 1 1 1 Course Details[1] and Overview[1]
2 08/20
 2, 3 2, 3.1 - 3.4 2, 3.1 - 3.4 Agents[2], Solving Problems by Search[2]
3 08/25
 4 3.5 - 3.6 3.5 - 3.6 Informed Search[2]
4
 08/27
 4 3.5 - 3.6 3.5 - 3.6
 Informed Search (contd.), Notes on Implementation[1]
5
 09/01
 6 5 5
 Game Playing[2], Alpha - Beta Pruning[3]

09/03


EXAM 1
6
 09/08
 6 5
 5
 Non - Deterministic Games
7
 09/10
 5 6
 6
 Constraint Satisfaction Problems[2]
8
 09/15
 5 6 6
 CSP (contd.)
9
 09/17
 7
 7
 7
 Knowledge and Logic Reasoning[2], Inference by Enumeration
10
 09/22
 7
 7
 7
 Forward and Backward Chaining, Resolution
11
 09/24
 8.1-8.3 8.1-8.3 8.1-8.3
First Order Logic[3]

09/29


EXAM 2
12
 10/01
 9.1, 9.2 9.1, 9.2 9.1, 9.2 Unification & FC/BC[2]
13
 10/06
 11 10 11
 Planning[3], Planning[2]
14
 10/08
 11
 10
 11
 Planning (Contd.)
15
 10/13
 12 11 11
 Conditional Planning and Replanning[3], Conditional Planning and Replanning[2]
16
 10/15
 13 13 12
 Probablity[2]
17
 10/20
 13 13 12
 Prior and Posterior Probablites[3]
18
 10/22
 14.1 - 14.4 14.1 - 14.4 13.1-13.4 Bayesian Networks[3], Bayesian Networks[2]

10/27


EXAM 3
19
 10/29
 18.1-18.3 18.1-18.3 19.1-19.3 Learning[3], Learning[2]
20
 11/03
 18.1-18.3 18.1-18.3 19.1-19.3
 Decision Trees[3]
21
 11/05
 18.1-18.3 18.1-18.3 19.1-19.3 Practical Issues with Decision Trees[3]
22
 11/10
20.3 20.3 Bayesian Classifiers[3]
23
 11/12
20.3 20.3 Probabilty Estimations
24
 11/17
 18.8.1 19.7.1
 Nearest Neighbor Classifiers[3]
25
 11/19
 20.5 18.6.4, 18.7 19.6.4, 21.1
 Neural Networks[2], Neuron Architeture[1][4],  Backpropogation Learning[3]

11/24


EXAM 4

11/26


THANKSGIVING HOLIDAY - NO CLASS

12/01


Final Exam Review Session, Final Q & A

12/03 - 12/09


FINAL EXAM WEEK - 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)

Schedule Changes