Hi David It seems that all you are asking for are the capabilities of Mathematica or Maple or some other CAS. A quick Google reveals that there is a CAS written in Python, called SAGE. That might be a good place to start; but I'll admit that I know nothing about it.
I'm with Robin Becker on this one, if GP is good enough for your problem, then the answers it produces should be good enough. Set the fitness criteria in favour of shorter rather than longer expressions and let you system run a little longer. Not only do you avoid having to integrate into your system a novel library, you avoid a world of pain trying to decide whether or not x**2 is 'simpler' than x*x, (is x**4 'simpler' than (x**2)*(x**2) ?) and making sure that you don't define any circular simplification rules. If you don't like the computer algebra approach, you could google for 'program transformation' and follow some of the links. Good luck ! Mark Westwood On 26 Jun, 12:06, DavidM <[EMAIL PROTECTED]> wrote: > On Tue, 26 Jun 2007 11:11:39 +0100, Robin Becker wrote: > > I have seen this sort of evolution strategy in the past and it's very wrong > > to > > attempt to simplify outside the genetic framework. The implication is that > > you > > know better than the overall fitness requirement. The additional > > expressions and > > redundancies allow for extra mutation and combination possibilities which > > is a > > good thing for the whole population. If you must, add the requirement to the > > target ie give extra fitness points to organisms which perform efficiently. > > I'm sorry, but there's something important I forgot to mention - I only > want to do the simplification *after* a winning successful organism has > evolved and satisfied the fitness function. -- http://mail.python.org/mailman/listinfo/python-list