If you have a savedchromes file with good ANNs in it, and you want to 
see some details of their behavior, do the following:

set popSize to 21  (one more than the number of chromosomes in 
savedchromes), set genLimit  and verbose to 1.
Then copy any small file to "showUpdates".  4Play, and waybak, contain a 
"file command" facility, allowing the presence of certain file names to 
have some effect.  (This was done to allow commands during execution, my 
creating, deleting or renaming files.)  When there is a file called 
"showUpdates" present, then the fitness function outputs some additional 
information.

I have just uploaded to the SVN repository a slightly revised version of 
fitness.c.  It will show one additional tidbit of information.  Here is 
an example, first the waybak.ini file, then the run output:

C:\C\waybak>type waybak.ini
       minSteps          3
       maxSteps          3
        popSize       21
       genLimit       1
        maxTime        2.5
      toDieFrac   0.933171
         mutmax   1.551407
     mutDecline   0.999918
           seed          0
        trigger        1.0
        neurons          6
     maxUpdates         34
        mutProb   0.971163
      crossProb   0.983983
  updatePenalty   0.000223
 weightSizeInit   0.866088
       stagnant         39
   altDeathProb          0
        verbose        1

C:\C\waybak>wb
waybak Version 0.1
     The waybak.ini file has these values:
minSteps      3.0000
maxSteps      3.0000
popSize     21.0000
genLimit      1.0000
maxTime      2.5000
toDieFrac      0.9332
mutmax      1.5514
mutDecline      0.9999
seed      0.0000
trigger      1.0000
neurons      6.0000
maxUpdates     34.0000
mutProb      0.9712
crossProb      0.9840
updatePenalty      0.0002
weightSizeInit      0.8661
stagnant     39.0000
altDeathProb      0.0000
verbose      1.0000
20 chromosomes imported

Run length:   2.50 min.   seed is 1152466447   There are 2 inputs, 6 
neurons.
Population 21  initial population RAM 4536  chromosome size 54

countWeights() says: 54
 ANN 0   correct 12   max 24   ANNupdates 48
 ANN 1   correct 24   max 24   ANNupdates 48
 ANN 2   correct 24   max 24   ANNupdates 48
 ANN 3   correct 23   max 24   ANNupdates 48
 ANN 4   correct 24   max 24   ANNupdates 48
 ANN 5   correct 22   max 24   ANNupdates 48
 ANN 6   correct 22   max 24   ANNupdates 48
 ANN 7   correct 24   max 24   ANNupdates 48
 ANN 8   correct 22   max 24   ANNupdates 48
 ANN 9   correct 23   max 24   ANNupdates 48
 ANN 10   correct 24   max 24   ANNupdates 48
 ANN 11   correct 24   max 24   ANNupdates 48
 ANN 12   correct 24   max 24   ANNupdates 49
 ANN 13   correct 23   max 24   ANNupdates 48
 ANN 14   correct 24   max 24   ANNupdates 48
 ANN 15   correct 24   max 24   ANNupdates 48
 ANN 16   correct 23   max 24   ANNupdates 48
 ANN 17   correct 23   max 24   ANNupdates 48
 ANN 18   correct 23   max 24   ANNupdates 48
 ANN 19   correct 20   max 24   ANNupdates 48
 ANN 20   correct 21   max 24   ANNupdates 48
best ANN is 1   0 gens since improve   wins 0.500 to 0.9996   Histogram:
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 3 0 6 0 9
After 0 seconds, gen 1 tested.  mutmax is 1.551  highCount 8  in 0
mean 0.938  mode 0.991  rng 0.500  doomed 12


waybak Version 0.1 has just finished execution.

The best ANN had a fitness value of 0.9996 and chromosome size of 54.
The run lasted    0.00 minutes and covered 1 generations.
Some parameter values are:
neurons 6
popSize 21
seed 1152466447
maxTime   2.50
stagnant 39
altDeathProb 0
mutDecline 0.99992
mutProb 0.97116
crossProb 0.9840
trigger 1.0000
mutmax  declined  from   1.551 to  1.551
toDieFrac changed from  0.933 to  0.933
The best fitness did not change during the run.

-- 
I'm proud of http://ANNEvolve.sourceforge.net.  If you want to write software, 
or articles, or do testing or research for ANNEvolve, let me know.  



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