An optimization of a black-only playing variant of the GNU-chess program was completed over approximately five weeks using a genetic algorithm simulation with 50 generations. The simulation showed that the average and best fitness in the population increased over time based on linear regression. The optimized version of GNU-chess obtained a higher fitness score of 0.592 compared to the original version's score of 0.456 when playing black against the original program in 40 games.

1. Result
At first stage of the current set of experiments for ℓ=12,
the optimization of a black-only playing variant of
the GNU-chess program has been completed with a
γ=50 generation genetic algorithm simulation over the
course of approximately five weeks. Figure 1 shows
the measured average fitness and the best fitness in the
population as well as the associated linear regression
lines. The latter show a strictly positive slope. shows the 12 stretching factors
used for the
positive resp. negative evaluation-coefficients of the
six types of chess-pieces obtained for the best optimized
version of GNU-chess in this genetic algorithm
simulation. The latter program obtains a fitness value
of 0.592 in the genetic algorithm simulation over 40
games playing black against the original GNU-chess
program compared to 0.456 for the original GNU-chess
program playing black against another copy of itself.
Fitness is defined here as the percentage of wins for
a phenotype plus half the percentage of draws playing
against the original GNU-chess program.