In analyzing my data I wanted to classify it with a naive Bayesian classifier. I wasn't sure I had the math right, so I wrote a tiny abstract classifier to test with. The code is pretty cool:
AI Related Ruby Extensions This page will maintain list of AI related extensions/modules/gems for the Ruby programming language. Please contact me if you know something I missed.
If you are starting with Neural Networks you should check out my online book on the subject. It contains over 300 pages of information on Neural Network Programming in Java. You can access it here.
This project contains Naive and Fishers bayesian classifiers, as described in Toby Segaran's book "Programming Collective Intelligence." The book has python implementations; this is a Java implementation.
R. Schank, and R. Abelson. Thinking: Readings in Cognitive Science, Proceedings of the Fourth International Joint Conference on Artificial Intelligence, page 151-157. Tbilisi, USSR, (1975)
A. Newell, and H. Simon. Communications of the ACM, 19 (3):
113-126(March 1976)p. 116:
"The Physical Symbol System Hypothesis. A physical
symbol system has the necessary and sufficient
means for general intelligent action."
p. 120:
"Heuristic Search Hypothesis. The solutions to
problems are represented as symbol structures.
A physical symbol system exercises its intelligence
in problem solving by search--that is, by
generating and progressively modifying symbol
structures until it produces a solution structure."
p. 121:
"To state a problem is to designate (1) a test
for a class of symbol structures (solutions of the
problem), and (2) a generator of symbol structures
(potential solutions). To solve a problem is
to generate a structure, using (2), that satisfies
the test of (1).".