Just in case it helps, I ported the code of Norvigs Paradigms of Artificial Intelligence Programming chapter 8 (integrals and derivates) for a collage course. It passes all the tests proposed by Norvig in his book, includes an expression parser written in Parsec and has a small libreadline interpreter. I as well have a pretty bad written report (done in a hurry before the deadline) but could be useful to understand the differences between the Norvigs implementation and my port. On 3/19/07, Adam Wyner wrote:

For the Haskell and AI work, we ought to consider AI programming books in addition to Russell and Norvig:

/Paradigms of AI Programming: Case Studies in Common Lisp/, P. Norvig, 1991. /Prolog Programming for Artificial Intelligence/, I. Bratko, 1990./ Artificial Intelligence Techniques in Prolog/, Y. Shoham, 1994.

Perhaps there are newer additions (e.g. Bratko), but the problems and solutions from these languages are presented. We can build on them rather than starting from scratch or even just the theoretical outline of Russell and Norvig.

Adam

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I would also recommend Mitchell, Machine Learning. I have quite a lot of Haskell code for stuff in this book, which I'm currently polishing for publishing. (For example, I'm rather proud of my thirty line neural network code.)