I presume that you are talking about converting the tree to a java source file and then compiling it and then executing it? This surely is going to be slow. And then, ECJ is already in java. So what would this step save. Symbolic regression can be made fast by opting for vector processing/evaluation by the interpreter. Much further improvements may be made by employing subtree caching. There is a paper by Maarten Keijzer that explains on this.
----- Original Message ----
From: Ondrej Pacovsky <[log in to unmask]>
To: [log in to unmask]
Sent: Saturday, September 27, 2008 3:29:43 AM
Subject: runtime complilation for expensive eval ?
I was wondering whether someone tried converting the GP individual to
java (or other) code (perhaps by the ECJ to Java converter) and
compiling it before actually running the evaluation. This is of course
quite slow, but for symbolic regression on many training values could be
interesting. Thinking of 10^3 and more evals per individual per generation.