I think we all agree that Lisp would be ideal for AI, given a medium
or long-term exposure, but for an introductory class to varied
branches of AI, we could do worse than Python, an easy to read
language with various numerical and AI libraries (PyEvolve, for
example. http://pyevolve.sourceforge.net/0_6rc1/). And it's dead
simple to start using it with IDLE or the REPL. After all, the class
is not about teaching Python or Lisp, it's about teaching AI concepts.
Even Java has been used this gentle introduction to genetic
programming: http://www.gp-field-guide.org.uk/. In fact, it might be
even better to start with a no-brainer language like Python.

Also if I may digress a bit, we have a tendency to forget that what
works for us best might not be what works best for other. Lisp simply
is not for everybody, maybe not even for most people, and that's ok.

On Aug 13, 1:36 pm, Lee Spector <lspec...@hampshire.edu> wrote:
> On the other hand I prefer to work in Lisp (Common Lisp, Scheme, Clojure), 
> but my main project these days involves evolving Push programs rather than 
> Lisp programs, for a bunch of reasons related to evolvability -- 
> seehttp://hampshire.edu/lspector/push.htmlif you really want to know. I 
> prefer to work in Lisps because they make it simpler to write code that 
> manipulates program-like structures (however they end up being "executed") 
> and because I like Lisps better than most other languages for a slew of other 
> reasons. But my evolved code is executed on a Push interpreter implemented in 
> the host language and there are Push-based GP systems in many languages (C++, 
> Java, Javascript, Python, several Lisps). The language choice really just 
> affects software engineering and workflow issues, not the fundamental power 
> of the system to evolve/learn.

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