```Hello everyone,

I'm *very* new to ECJ, so my apologies if I have done something stupid.
I would, however, very much appreciate someone telling me where I've
gone wrong!

I have run the parity examples provided with ECJ and I'm confused with
the results.  I have tried to reproduce some of the experiments in
Koza's second book.  My expectation was that I could use the parity
examples provided with ECJ to get similar results to chapter 6 of GPII
which generally concludes that the use of ADFs is a good thing for this
domain.

As I understand it there are two configuration scripts for even-n-parity
in ECJ: one is for standard Koza-style GP (his first book), and the
other is for standard Koza-style GP with ADFs (his second book).  The
defaults are for even-4-parity with standard GP, and even-3-parity for

I executed 500 runs (ECJ is really quite quick!) of the even-4-parity
example with a population size of 500.  (I modified the population size
by editing "pop.subpop.0.size" in ec/simple/simple.params.)   It
produced a success rate of 32.4% (162/500 successful runs) by generation 50.

I then executed 500 runs of the even-4-parity problem but this time with
changed "eval.problem.bits" to 4, and "gp.fs.0.size" to 10,
"gp.fs.1.size" to 10 and "gp.fs.2.size" to 11 (as per the instructions
in the file).  Of the 500 runs only 3 (0.6%!!!) found a solution after
50 generations.

So, to summarize, Standard GP scored 32.4% while GP with ADFs scored
0.6%.  From Koza's second book on GP (page 181), this was not what I
expected to get.  I expected GP with ADFs to outperform standard GP on
this problem domain.  I sat around scratching my head trying to work out
what I had done wrong, however nothing but hair came out ;o)

I've just repeated this process with even-3-parity, again with a
population size of 500.  This time I did not modify adf.params from it's
original source.  I followed the instructions in parity.params to reduce
it from even-4 to even-3.  This time standard GP found a solution by
generation 50 in 100% of the 100 runs I executed.  In comparison GP with
ADFs found solutions in just 46% (46/100) of the runs.  Again this was
not what I expected.  Page 177 of GPII tells me that I should expect
ADFs to outperform Standard GP with a computational effort ratio of
about 1.5.  The two computational efforts scores were 7,000 (for
standard GP) and 161,203 (for ADFs), or a ratio of about 0.04.

I wondered if the issue was that I'd scaled down the population size.
So I modified simple/simple.params (but still working with
even-3-parity) so that the population size was now 16,000---just as Koza
used.  I had some problems here with a "java.lang.OutOfMemoryError: Java
heap space" exception, but sufficient runs completed anyway.

Standard GP found solutions in 100% (84/84) of the runs that terminated
normally (i.e. without the exception).  Every one of the solutions were
found by generation 3, giving a minimum computational effort of 64,000.
Koza's result was 96,000.

GP with ADFs also found solutions in 100% (96/96) of its normal runs.
However this only happened by generation 9, giving a computational
effort of 160,000.  In Koza's work ADFs beat Standard GP... not the
other way around!

So from all this I'm left convinced that I've made some fundamental
mistake in every one of these setups.  I've no idea what I'm doing wrong
and would love some assistance!

I've searched the archives of this list and didn't see anything about
this topic, but once again I apologize if this is obvious.