I'm working on a regression problem.  The goal is to have GP evolve a
comparator function for ordering lists.

But the problem is that I changed the way I score the fitness.  Originally I
would give a score of 0.0 if the correct result was first in the list.  Now
I changed so that the score is the natural log of how far from the first
position that the correct result is in the hopes that a more continuous
fitness score would improve evolution.

The head-scratching problem I have is that with the new fitness score I
always get a evolution that halts after one generation:

Initializing Generation 0
Subpop 0 best fitness of generation: Fitness: Standardized=0.0 Adjusted=1.0
Hits=0
Found Ideal Individual
Subpop 0 best fitness of run: Fitness: Standardized=0.0 Adjusted=1.0 Hits=0

I always had multiple generations previously.  And I've debugged the code to
make sure that setStandardizedScore is being passed a value greater than
zero.  So why does it say that the standardized score is 0 when I know I'm
passing it non-zero values?

I've attached the entire class for reference.  But the gist is that:

sum += 1.0f;

changed to :

sum += (float) Math.log(position + 1);


Courtney Falk