AI-PSO
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lib/AI/PSO.pm view on Meta::CPAN
# for users to implement their own cache since they are passed the same array of values.
#
sub compute_fitness(@) {
my (@values) = @_;
my $return_fitness = 0;
# no strict 'refs';
# if(defined(&{"main::$user_fitness_function"})) {
# $return_fitness = &$user_fitness_function(@values);
# } else {
# warn "error running user_fitness_function\n";
# exit 1;
# }
# use strict 'refs';
$return_fitness = $user_fitness_function->call(@values);
return $return_fitness;
}
lib/AI/PSO.pm view on Meta::CPAN
#
# get_index_of_neighbor
#
# - returns the index of Nth neighbor of the index for particle P
# ==> A neighbor is one of the next K particles following P where K is the neighborhood size.
# So, particle 1 has neighbors 2, 3, 4, 5 if K = 4. particle 4 has neighbors 5, 6, 7, 8
# ...
#
sub get_index_of_neighbor($$) {
my ($particleIndex, $neighborNum) = @_;
# TODO: insert error checking code / defensive programming
return ($particleIndex + $neighborNum) % $numParticles;
}
#
# get_index_of_best_fit_neighbor
# - returns the index of the neighbor with the best fitness (when given a particle index)...
#
sub get_index_of_best_fit_neighbor($) {
my ($particleIndex) = @_;
my $bestNeighborFitness = 0;
my $bestNeighborIndex = 0;
my $particleNeighborIndex = 0;
for(my $neighbor = 0; $neighbor < $numNeighbors; $neighbor++) {
$particleNeighborIndex = &get_index_of_neighbor($particleIndex, $neighbor);
if(&compute_fitness(@{$particles[$particleNeighborIndex]{bestPos}}) > $bestNeighborFitness) {
$bestNeighborFitness = &compute_fitness(@{$particles[$particleNeighborIndex]{bestPos}});
$bestNeighborIndex = $particleNeighborIndex;
}
}
# TODO: insert error checking code / defensive programming
return $particleNeighborIndex;
}
#
# clamp_velocity
# - restricts the change in velocity to be within a certain range (prevents large jumps in problem hyperspace)
#
sub clamp_velocity($) {
my ($dx) = @_;
if($dx < $deltaMin) {
( run in 0.283 second using v1.01-cache-2.11-cpan-65fba6d93b7 )