CS 662 resources:

Announcements:

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Regrading: If you feel that your homework was not graded correctly, you should return it to me, along with a written explanation of the error. I will evaluate this explanation and award any necessary points.

Midterms:

Solutions to midterm 2 can be found here . Total points: 150 Mean: 119 Median: 126

Solutions to midterm 1 can be found here . Total points: 150 Mean: 120 Median: 118 StDev: 15

Midterm 1 will be held Monday, October 13. It is in class, closed-book and closed-notes. You can find a list of potential topics here.

Readings:

A list of readings from AIMA, 2nd edition, by week.

Week of 9/3: 1.1 (pp 1-5), 1.4 (pp 27-28) (the rest of chapter 1 is also very interesting reading)
Week of 9/8: Chapter 2: 2.1-2.4, pp 32-54
Week of 9/15: 3.1-3,2 (pp 59-68), 3.3-3.5 (pp 69-83)
Week of 9/22: 4.1-4,3: (pp 94-118).
Week of 9/27: provided below.
Week of 10/6: 6.1-6.3 (pp 161-171)
Week of 10/13: Midterm 1.
Week of 10/20: Logic. 7.1-7.5 (197-220), Intro to Jess (10/20), plus intro to First-order logic (10/22) Required reading: R & N: Ch 8 (pp 240-268)
Week of 10/27: More first-order logic, advanced Jess programming Required reading: R & N, Ch 9.
Week of 11/3: Planning. Reading: R & N: 11.1-11.3, pp 375-394, decision trees. 18.1-18.3 pp 649-664.
Week of 11/10: Probability. 13.1-13.6. pp 462-482. Bayesian learning. reading provided.
Week of 11/17- Bayesian Networks. R & N 14.1-14.4. Utility theory and Decision Networks. 16.1-16.6.
Week of 12/1: Neural Networks. R & N 20.5
Week of 12/8: MDPs and Reinforcement Learning. R & N 17.1-17.3, 21.1-21.3

Lectures:

Slides from Class 1: 9/3/03
Slides from Class 2 & 3: Agents and Environments 9/8/03 and 9/10/03.
Slides from Class 4 & 5: Uninformed Search 9/15/03 and 9/17/03
Slides from Class 6: Heuristic Search 9/22/03
Slides from Class 7: Local Search 9/22/03
Slides from Class 8: Genetic Algorithms 9/29/03
Slides from Class 9: Classifier Systems 10/1/03
Slides from Class 10: Adversarial Search 10/6/03
Slides from Class 11: Intro to Propositional Logic 10/15/03
Slides from Class 12: Resolution in Propositional Logic and Introduction to Jess 10/20/03
Slides from Class 13: Introduction to First-order Logic 10/22/03
- Here is the Jess code and notes from the lecture.
Slides from Class 14: Inference in First-order Logic 10/27/03
Slides from Class 15: Planning 11/3/03
Slides from Class 16: Decision Trees 11/5/03
Slides from Class 17: Probability 11/10/03
Slides from Class 18: Bayesian Learning 11/12/03
Slides from Class 19: Bayesian Networks 11/17/03
Slides from Class 20: Utility and Decision Networks 11/19/03
Slides from Class 21: Neural Networks 12/1/03
Slides from Class 22: Neural Networks II 12/3/03
Slides from Class 23: Markov Decision Processes 12/8/03
Slides from Class 24: Q-learning 12/10/03

Links:

Jess resources:

Some notes on working with Jess.
The Jess homepage
The Jess manual. Note that we'll just be using the Jess language itself, not the Java extensions, so ignore all the stuff about Java.
Jess functions These are the built-in functions that Jess has.
The Jess reference manual A description of the language features. Again, skip over the Java stuff.
The CLIPS User's guide. Jess is a Java port of CLIPS. This document is a user's guide to clips, with lots of examples. Almost all the language-relevant material in this manual applies to Jess.

GA/GP readings:

A Genetic Algorithm Tutorial Darrell Whitley. Statistics and Computing (4):65-85, 1994
More will be provided in class.

Python links:

The Python Home Page A wealth of information.
A Python tutorial, written by Guido van Rossum, the original developer of Python.
Another Python Intro
Safari: O'Reilly's online library. Online access to all of O'Reilly's books, including their Python books. (Note: this is a subscription service, but well worth the $10/month, IMHO)
A Python Quick Reference
Python Online. This one's about Monty Python, rather than Python the language, but it's fun, and might explain why you see so many "spam" examples in Python tutorials.

AIMA links