GP & Linux
I’ve been immersed in getting a Genetic Programming implementation up and running over the last few weeks. The combination of OCaml’s pattern matching and type inferencing have really come through for me, allowing me to comfortably experiment with alterations to the foundations of the system.
In the process, I’ve read quite a few research papers. CiteSeer has proven very helpful and Google just announced Google Scholar which looks promising.
Genetic Programming is extremely computationally expensive and as a result I’ve been doing quite a bit of CPU profiling lately. OCaml unfortunately doesn’t support profiling on Windows, so I’ve been spending some quality time with Linux. I’ve been surprised by how nice the latest distributions are, particularly the “sarge” release of Debian. In fact, for the first time, I now consider Linux a credible alternative to Windows on the desktop.
November 19th, 2004 at 8:06 am
OS X is a nice alternative to both, as long as your hardware budget has a little slop in it.
February 17th, 2005 at 7:09 pm
Believe me, I’m tempted to pick up an OSX box! I suspect that once Apple announces Tiger I’ll pick up a Mac Mini. Now if they would just put 2 mouse buttons on the Powerbooks…
August 8th, 2005 at 4:26 am
See http://www.paraschopra.com/sourcecode/GP/index.php for a implementation of GP in Python…
May 15th, 2006 at 11:21 am
Hello,
if you’re interested in Genetic Algorithms, Genetic Programming or multi-objective, randomized heuristic search algorithms, you would maybe like to have a look at the Distributed Genetic Programming Framework. This LGPL-licensed, open source Java project can be found in the internet at http://dgpf.sourceforge.net/.
It also allows you to distribute the searches over a network and let different search algorithms (GA, Hill Climbing, ...) interact and form a heterogeneous search.