CS 662 Resources


Announcements:

Solutions for Midterm 2 are now available.

An old midterm 2 is available here. Please ignore the questions on probability and utility; we'll cover these topics later in the semester. A version with answers can be found here.

Extra FOL practice problems can be found here.

Solutions to midterm 1 are here.

A sample midterm can be found here . (note: ignore question 6 - we haven't covered adversarial search yet.)

Solutions for this midterm can be found here.

A list of potential midterm topics can be found here .



Go here to sign up for the cs662 mailing list. (you must be on this list - please use an email address you check regularly.)

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.


Lectures and associated readings:
Date Topic Associated Reading Slides
August 24 Lecture 1: Introduction. What is AI? R & N: 1.1 pp 1-4, 26.1-2: pp 947-958 Full size
Printable
August 29 Lecture 2: Intro to Python Dive Into Python Chapters 2,3,6. Full size
Printable
August 31 Lecture 3: Agents and Environments R & N: Chapter 2: pp 32-58 Full size
Printable
September 5 Lecture 4: More Python Dive Into Python Chapters 4,5,8. Full size
Printable
September 7 Lecture 5: Search I: BFS, DFS, IDS R & N: 3.1-3.5 pp 59-83 Full size
Printable
September 12 Lecture 6: Search II: Greedy Search, A* R & N: 4.1-4.2 pp 94-109 Full size
Printable
September 14 Lecture 7: Constraint Satisfaction, Branch and Bound R & N: 5.1-5.2 pp 137-150 Full size
Printable
September 19 Lecture 8: Local Search and Genetic Algorithms R & N: 4.3 pp 110-119 Full size
Printable
September 21 Lecture 9: More GAs, midterm review TBD
September 26 Midterm 1 n/a
September 28 Lecture 10: Introduction to Knowledge Representation R & N: 7.1-7.5: pp 194-220 Full size
Printable
October 3 Lecture 11: First-order Logic R & N: 8.1-8.3: pp 240-258 Full size
Printable
October 5 Lecture 12: Inference and Rule-based systems R & N: 9.1-9.6: pp 272-300 Full size
Printable
October 10 Lecture 13: More inference, Ontologies R & N: 10.1, 10.2, 10.5, 10.6. pp 320-328, 344-354. Full size
Printable
October 12 Lecture 14: More ontologies, using Protege. Ontology Development 101
The Pizza Ontology Tutorial
Full size
Printable
October 17 Lecture 15: Planning R & N: 11.1-11.3: pp 375-395 Full size
Printable
October 19 Lecture 16: Decision Trees R & N 18.1-18.3. pp 649-664. Full size
Printable
October 24 Midterm review n/a
October 26 Midterm 2
October 31 Lecture 17: Introduction to Probability R & N 13.1-13.6: pp 462-481 Full size
Printable
November 2 Lecture 18: Bayesian Networks R & N 14.1, 14.2: pp 492-499. Full size
Printable
November 7 Lecture 19: Bayesian Learning R & N 20.1: pp 712-716 Full size
Printable
November 9 Lecture 20: Introduction to Machine Learning R & N: 20.1, 21.1: 712-716, 763-765 Full size
Printable
November 14 Lecture 21: Clustering Algorithms Mitchell, Chapter 8 (provided in class) Full size
Printable
November 16 Lecture 22: Utility and Value of Information R & N 16.1-16.3, 16.6: pp 584-591,600-603
Full size
Printable
November 21 Lecture 23: Markov Decision Processes R & N: 17.1-17.3: pp 613-625 Full size
Printable
November 23 Thanksgiving. No class n/a
November 28 Lecture 24: Neural Networks R & N 20.5: 736-748 Full size
Printable
November 30 Lecture 25: Neural Networks R & N 20.5: 736-748 Full size
Printable
December 5 Lecture 26: Review and Summary n/a

Sample code

Sample code from the intro to python lecture


Links


Protege Resources

GA/GP readings

Python links

AIMA links