Closed GoogleCodeExporter closed 9 years ago
This is normal. The reason you're seeing this behavior is that the fitness
function can not find suitable genes in the lower two quartiles and the
gene_server filters out any submitted genes that did not result in a trade.
In the gts.py script, each time the population is fully scored, the local
optima buffer captures the highest score. Local optima is detected when the
buffer is filled with the same score. This indicates that no further progress
is likely with the test population. And with the run_once option set when
launching gts.py, the script will 'expire' when this condition is reached.
So one reason your seeing greater expiration rates for the lower two quartiles
is that the local optima condition is triggered with the absolute minimum
number of population cycles required due to no advancement in fitness scores.
The second contributor is that the fitness function runs faster when no trade
positions are generated. This is because the fitness function code to manage
trade positions is never executed.
The reason the gene visualization for the first two quartiles are of differing
lengths is that the gene_server wont accept submissions for the lowest score:
if d['score'] != -987654321.12346:
Differences in performance between commits can probably be attributed to
changes in the gene_def config. I regularly change it for testing purposes.
Thanks for the issue submission, I'll add this note to the FAQ.
Original comment by brian.mo...@gmail.com
on 28 Dec 2012 at 8:25
Original issue reported on code.google.com by
andremos...@gmail.com
on 22 Dec 2012 at 7:01Attachments: