CS 5233: Artificial Intelligence, Fall 2007

Special Announcement for class on November 21, 2007

Instead of holding class in our usual classroom, we will experiment by holding class in this chatroom. For preparation, you should have a copy of the vision classnotes handy, and you should register a login name in advance in the chatroom.

Here is a transcript of our chat.

Syllabus and Assignments

Syllabus

The lab assignments will be agent oriented, i.e., students will write programs that interact with one or more other programs.  Since the interaction will be through standard input and standard output, any programming language should work.  Any hints from the instructor will be in C though. The initial set of programs that we will be working with can be downloaded as a tar file or a zip file (updated 11/02/07).

Lab 1 (a little hint) (a big hint), Lab 2, Lab 3 (example confusion matrix).

Homework 1, Homework 2, Homework 3, Homework 4.

Homework 5, Homework 6, Homework 7, Homework 8, Homework 9, Homework 10.

We will also be using a program called Prover9 that performs logical inference.

Official Prover9 Web Site, Introduction to Prover9, Prover9 Example 1, Prover9 Example 2, Prover9 Example 3, Wumpus Example.

Finally, I have made progress on adding natural language software (NLTK, the Natural Language ToolKit) to the course.

Official NLTK Web Site, Introduction to the NLTK, Wumpus Grammar Example, Helpful Python Functions, Semantics Example, NLTK Bug Fix.

Handouts (subject to change)

Iterative Deepening, A* Search, Alpha-Beta Pruning, Propositional Logic, Wumpus Inference, elim-bel Algorithm, Partial Planning Notes, Partial Planning Example, Learning Theory , Perceptron Mistake Bound, General Loss Bounds.

Notes (subject to change)

Agents, Search, Search Examples, Heuristic Search, Game Playing.

Logic, Knowledge Engineering, Probability.

Planning, Learning, Numerical Learning Algorithms, Neural Networks, Natural Language, Vision.

Other Stuff

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