package Algorithm::MasterMind::CGA_Partitions;
use warnings;
use strict;
use Carp;
use lib qw(../../lib
../../../lib
../../../../Algorithm-Evolutionary/lib
../../../Algorithm-Evolutionary/lib
../../Algorithm-Evolutionary/lib);
our $VERSION = sprintf "%d.%03d", q$Revision: 1.3 $ =~ /(\d+)\.(\d+)/g;
use base 'Algorithm::MasterMind::Canonical_GA';
use Algorithm::MasterMind qw(partitions);
sub issue_next {
my $self = shift;
my $rules = $self->number_of_rules();
my @alphabet = @{$self->{'_alphabet'}};
my $length = $self->{'_length'};
my $pop = $self->{'_pop'};
my $cga = $self->{'_ga'};
map( $_->evaluate( $self->{'_fitness'}), @$pop );
my @ranked_pop = sort { $b->{_fitness} <=> $a->{_fitness}; } @$pop;
my %consistent;
# print "Consistent in ", scalar keys %{$self->{'_consistent'}}, "\n";
if ( $self->{'_consistent'} ) { #Check for consistency
%consistent = %{$self->{'_consistent'}};
for my $c (keys %consistent ) {
my $match = $self->matches( $c );
if ( $match->{'matches'} < $rules ) {
delete $consistent{$c};
}
}
} else {
%consistent = ();
}
# print "Consistent out ", scalar keys %consistent, "\n";
while ( $ranked_pop[0]->{'_matches'} == $rules ) {
$consistent{$ranked_pop[0]->{'_str'}} = $ranked_pop[0];
shift @ranked_pop;
}
my $generations_equal = 0;
# The 20 was computed in NICSO paper, valid for normal mastermind
my $number_of_consistent = keys %consistent;
# print "Consistent new ", scalar keys %consistent, "\n";
while ( $number_of_consistent < 20 ) {
my $this_number_of_consistent = $number_of_consistent;
$cga->apply( $pop );
for my $p( @$pop ) {
my $matches = $self->matches( $p->{'_str'} );
# print "* ", $p->{'_str'}, " ", $matches->{'matches'}, "\n";
if ( $matches->{'matches'} == $rules ) {
# print "Combination ", $p->{'_str'}, " matches ", $p->{'_matches'}, "\n";
$consistent{$p->{'_str'}} = $p;
}
}
$number_of_consistent = keys %consistent;
if ( $this_number_of_consistent == $number_of_consistent ) {
$generations_equal++;
} else {
$generations_equal = 0;
}
# print "G $generations_equal $number_of_consistent \n";
last if ( ( $generations_equal >= 3 ) && ( $number_of_consistent >= 1 ) );
}
# print "After GA combinations ", join( " ", keys %consistent ), "\n";
$self->{'_consistent'} = \%consistent; #This mainly for outside info
if ( $number_of_consistent > 1 ) {
# print "Consistent ", scalar keys %consistent, "\n";
#Use whatever we've got to compute number of partitions
my $partitions = partitions( keys %consistent );
my $max_partitions = 0;
my %max_c;
for my $c ( keys %$partitions ) {
my $this_max = keys %{$partitions->{$c}};
$max_c{$c} = $this_max;
if ( $this_max > $max_partitions ) {
$max_partitions = $this_max;
}
}
# Find all partitions with that max
my @max_c = grep( $max_c{$_} == $max_partitions, keys %max_c );
# Break ties
my $string = $max_c[ rand( @max_c )];
# Obtain next
return $self->{'_last'} = $string;
} else {
return $self->{'_last'} = (keys %consistent)[0];
}
}
"Many blacks, 0 white"; # Magic true value required at end of module
__END__
=head1 NAME
Algorithm::MasterMind::CGA_Partitions - Solver using a Canonical GA
=head1 SYNOPSIS
use Algorithm::MasterMind::CGA_Partitions;
my $secret_code = 'EAFC';
my $population_size = 200;
my @alphabet = qw( A B C D E F );
my $solver = new Algorithm::MasterMind::CGA_Partitions { alphabet => \@alphabet,
length => length( $secret_code ),
pop_size => $population_size};
#The rest, same as the other solvers
=head1 DESCRIPTION
Uses L instance of canonical genetic algorithm to solve MM; as there
are two different fitness functions you can use; probably
C works better.
=head1 INTERFACE
=head2 initialize
Performs bookkeeping, and assigns flags depending on the
initialization values
=head2 new ( $options )
This function, and all the rest, are directly inherited from base
=head2 issue_next()
Issues the next combination
=head2 feedback()
Obtain the result to the last combination played
=head2 guesses()
Total number of guesses
=head2 evaluated()
Total number of combinations checked to issue result
=head2 number_of_rules ()
Returns the number of rules in the algorithm
=head2 rules()
Returns the rules (combinations, blacks, whites played so far) y a
reference to array
=head2 matches( $string )
Returns a hash with the number of matches, and whether it matches
every rule with the number of blacks and whites it obtains with each
of them
=head2 fitness( $individual )
Computes fitness summing the number of correct black and whites plus
the number of rules the combination meets times the length
=head2 fitness_orig( $individual )
Fitness proposed in the Applied and Soft Computing paper, difference
between the number of blacks/whites obtained by rules against the
secret code and by the combination against the combination in the
rule.
=head1 SEE ALSO
Other solvers: L and
L. Don't work as well, really.
=head1 AUTHOR
JJ Merelo C<< >>
=head1 LICENCE AND COPYRIGHT
Copyright (c) 2009, JJ Merelo C<< >>. All rights reserved.
This module is free software; you can redistribute it and/or
modify it under the same terms as Perl itself. See L.
=head1 DISCLAIMER OF WARRANTY
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