LISP, Perl and Smalltalk are all reflective languages that do what you need. I have to admit that I like Smalltalk, but the learning curve is weird, as it's not like anything else. Check out Squeak at squeak.org, and don't worry about being totally confused by it at first.
A lot of language based AI research was done in LISP. I think it was invented for it. Massive learning curve, as it's also totally unlike anything else.
The catch with using Perl is that large perl programs can easily become unreadable unless you really work at keeping them maintainable. Perl has had some performance issues with it's psuedo OO features - this may be less of an issue with perl 6 onwards, as I haven't kept up to date with it.
In my work (a long time ago) I used a special purpose language called CELLANG to generate the cellular automata core (in C), then added sockets to that (reading generated code is not fun as variable names are not people friendly and there are massive tables of pointers to things that you have to touch), and had that talking to perl programs that managed the genetic algorithm code that modified the weights and rules of the automata, the perl in turn called small C programs that handled changes to rules for the mobile agents.
As long as you stay in the core of perl performance can be quite good. I believe that lisp can be very fast.
Runtime speed is not great with smalltalk. This is offset by the quite incredible efficiency with which you can program in it - quite sophisticated programs can be done in very few lines, and because everything is live code the debug cycle is very efficient.
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