AI-ANN
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Revision History for ANN
0.008 2011-06-13 06:52:38 UTC
Add support for an Inline::C version of AI::ANN::Neuron::Execute.
This is the default.
Fix a few extra errors because of uninitialized values being sent to
the C code. If you're using the inline::c stuff, be careful that
you don't skip any necessary inputs.
0.007 2011-06-12 04:44:46 UTC
Add backprop, not tested.
Evolver now allows you to pass a coderef for mutation_amount. It
will be evaluated with no arguments. If you pass a number instead,
0.003 2011-05-31 01:09:32 UTC
Minor. Correct the perl version requirement.
0.002 2011-05-31 01:04:53 UTC
Make many obvious (to a computer, I hope) references to the fact
that this requires perl 5.14, to prevent the bloody annoying
CPAN Testers emails. Note that I chose to do this rather than
make the module compatible with earlier versions.
Add two parameters for min and max neuron output values, default to
0 and 1. Conveniently, forget to actually implement that.
Less conveniently, remember to implement the above.
While implementing the above, also implement an activation function
in the form of a coderef passed to the AI::ANN constructor.
Add the Evolver module, and tests for it. Ensure that the AI::ANN
objects that Evolver returns have the same parameters as did the
original.
_Inline/build/AI/ANN/Neuron_6185/Makefile view on Meta::CPAN
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lib/AI/ANN.pm view on Meta::CPAN
has 'input_count' => (is => 'ro', isa => 'Int', required => 1);
has 'outputneurons' => (is => 'ro', isa => 'ArrayRef[Int]', required => 1);
has 'network' => (is => 'ro', isa => 'ArrayRef[HashRef]', required => 1);
# network is an arrayref of hashrefs. Each hashref is:
# object => AI::ANN::Neuron
# and has several other elements
has 'inputs' => (is => 'ro', isa => 'ArrayRef[Int]');
has 'rawpotentials' => (is => 'ro', isa => 'ArrayRef[Int]');
has 'minvalue' => (is => 'rw', isa => 'Int', default => 0);
has 'maxvalue' => (is => 'rw', isa => 'Int', default => 1);
has 'afunc' => (is => 'rw', isa => 'CodeRef', default => sub {sub {shift}});
has 'dafunc' => (is => 'rw', isa => 'CodeRef', default => sub {sub {1}});
has 'backprop_eta' => (is => 'rw', isa => 'Num', default => 0.1);
around BUILDARGS => sub {
my $orig = shift;
my $class = shift;
my %data;
if ( @_ == 1 && ref $_[0] eq 'HASH' ) {
%data = %{$_[0]};
} else {
%data = @_;
}
lib/AI/ANN/Evolver.pm view on Meta::CPAN
use strict;
use warnings;
use Moose;
use AI::ANN;
use Storable qw(dclone);
use Math::Libm qw(tan);
has 'max_value' => (is => 'rw', isa => 'Num', default => 1);
has 'min_value' => (is => 'rw', isa => 'Num', default => 0);
has 'mutation_chance' => (is => 'rw', isa => 'Num', default => 0);
has 'mutation_amount' => (is => 'rw', isa => 'CodeRef', default => sub{sub{2 * rand() - 1}});
has 'add_link_chance' => (is => 'rw', isa => 'Num', default => 0);
has 'kill_link_chance' => (is => 'rw', isa => 'Num', default => 0);
has 'sub_crossover_chance' => (is => 'rw', isa => 'Num', default => 0);
has 'gaussian_tau' => (is => 'rw', isa => 'CodeRef', default => sub{sub{1/sqrt(2*sqrt(shift))}});
has 'gaussian_tau_prime' => (is => 'rw', isa => 'CodeRef', default => sub{sub{1/sqrt(2*shift)}});
around BUILDARGS => sub {
my $orig = shift;
my $class = shift;
my %data;
if ( @_ == 1 && ref $_[0] eq 'HASH' ) {
%data = %{$_[0]};
} else {
%data = @_;
}
lib/AI/ANN/Evolver.pm view on Meta::CPAN
=head1 METHODS
=head2 new
AI::ANN::Evolver->new( { mutation_chance => $mutationchance,
mutation_amount => $mutationamount, add_link_chance => $addlinkchance,
kill_link_chance => $killlinkchance, sub_crossover_chance =>
$subcrossoverchance, min_value => $minvalue, max_value => $maxvalue } )
All values have a sane default.
mutation_chance is the chance that calling mutate() will add a random value
on a per-link basis. It only affects existing (nonzero) links.
mutation_amount is the maximum change that any single mutation can introduce.
It affects the result of successful mutation_chance rolls, the maximum
value after an add_link_chance roll, and the maximum strength of a link
that can be deleted by kill_link_chance rolls. It can either add or
subtract.
add_link_chance is the chance that, during a mutate() call, each pair of
unconnected neurons or each unconnected neuron => input pair will
lib/AI/ANN/Evolver.pm view on Meta::CPAN
for new links.
=head2 mutate_gaussian
$evolver->mutate_gaussian($network)
Returns a version of $network modified according to the Gaussian mutation
rules discussed in X. Yao, Evolving Artifical Neural Networks, and X. Yao
and Y. Liu, Fast Evolution Strategies. Uses the gaussian_tau and
gaussian_tau_prime values from the initializer if they are present, or
sane defaults proposed by the above. These are both functions of 'n', the
number of inputs to each neuron with nonzero weight.
=head1 AUTHOR
Dan Collins <DCOLLINS@cpan.org>
=head1 COPYRIGHT AND LICENSE
This software is Copyright (c) 2011 by Dan Collins.
lib/AI/ANN/Neuron.pm view on Meta::CPAN
}
END_C
has 'id' => (is => 'rw', isa => 'Int');
has 'inputs' => (is => 'rw', isa => 'ArrayRef', required => 1);
has 'neurons' => (is => 'rw', isa => 'ArrayRef', required => 1);
has 'eta_inputs' => (is => 'rw', isa => 'ArrayRef');
has 'eta_neurons' => (is => 'rw', isa => 'ArrayRef');
has 'inline_c' => (is => 'ro', isa => 'Int', required => 1, default => 1);
around BUILDARGS => sub {
my $orig = shift;
my $class = shift;
my %data;
if ( @_ >= 2 && ref $_[0] && ref $_[1]) {
%data = ('inputs' => $_[0], 'neurons' => $_[1]);
$data{'eta_inputs'} = $_[2] if defined $_[2];
$data{'eta_neurons'} = $_[3] if defined $_[3];
} elsif ( @_ >= 3 && ref $_[1] && ref $_[2]) {
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