AI-Evolve-Befunge
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lib/AI/Evolve/Befunge/Population.pm view on Meta::CPAN
my $usage = 'Usage: $population->new_code_fragment($length, $density);';
croak($usage) unless ref($self);
croak($usage) unless defined($length);
croak($usage) unless defined($density);
my $physics = $self->physics;
push(@safe, sort keys %{$$physics{commands}})
if exists $$physics{commands};
my $rv = '';
foreach my $i (1..$length) {
my $chr = ' ';
if(rand()*100 < $density) {
$chr = $safe[int(rand()*(scalar @safe))];
}
$rv .= $chr;
}
return $rv;
}
=head2 pair
my ($c1, $c2) = $population->pair(map { 1 } (@population));
my ($c1, $c2) = $population->pair(map { $_->fitness } (@population));
Randomly select and return two blueprints from the blueprints array.
Some care is taken to ensure that the two blueprints returned are not
actually two copies of the same blueprint.
The @fitness parameter is used to weight the selection process. There
must be one number passed per entry in the blueprints array. If you
pass a list of 1's, you will get an equal probability. If you pass
the critter's fitness scores, the more fit critters have a higher
chance of selection.
=cut
sub pair {
my $self = shift;
my @population = @{$self->blueprints};
my $popsize = scalar @population;
my $matchwheel = Algorithm::Evolutionary::Wheel->new(@_);
my $c1 = $matchwheel->spin();
my $c2 = $matchwheel->spin();
$c2++ if $c2 == $c1;
$c2 = 0 if $c2 >= $popsize;
$c1 = $population[$c1];
$c2 = $population[$c2];
return ($c1, $c2);
}
=head2 generation
my $generation = $population->generation();
$population->generation(1000);
Fetches or sets the population's generation number to the given value.
The value should always be numeric.
When set, as a side effect, rehashes the config file so that new
generational overrides may take effect.
=cut
sub generation {
my ($self, $gen) = @_;
if(defined($gen)) {
$$self{generation} = $gen;
$self->reload_defaults();
}
return $$self{generation};
}
1;
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