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lib/AI/NNFlex/Reinforce.pm  view on Meta::CPAN

##########################################################
# AI::NNFlex::Reinforce
##########################################################
# NNFlex learning module
# this is a bit of an experimental one. All it does is
# Reinforce the weight depending on the sign & activity
# of the node, sort of a gross oversimplification of a
# neuron.
#
##########################################################
# Versions
# ========
#
# 1.0	20041125	CColbourn	New module
# 1.1	20050116	CColbourn	Fixed reverse @layers
#					bug reported by GM Passos
#
# 1.2	20050218	CColbourn	Mod'd to change weight
#					addressing from hash to
#					array for nnf0.16
#
# 1.3	20050307	CColbourn	repackaged as a subclass
#					of nnflex
#
##########################################################
# ToDo
# ----
#
#
###########################################################
#

package AI::NNFlex::Reinforce;
use AI::NNFlex;
use AI::NNFlex::Feedforward;
use base qw(AI::NNFlex AI::NNFlex::Feedforward);
use strict;


###########################################################
#AI::NNFlex::Reinforce::learn
###########################################################
sub learn
{

	my $network = shift;

	my @layers = @{$network->{'layers'}};

	# no connections westwards from input, so no weights to adjust
	shift @layers;

	# reverse to start with the last layer first
	foreach my $layer (reverse @layers)
	{
		my @nodes = @{$layer->{'nodes'}};

		foreach my $node (@nodes)
		{
			my @westNodes = @{$node->{'connectedNodesWest'}->{'nodes'}};
			my @westWeights = @{$node->{'connectedNodesWest'}->{'weights'}};
			my $connectedNodeCounter=0;
			foreach my $westNode (@westNodes)
			{
				my $dW = $westNode->{'activation'} * $westWeights[$connectedNodeCounter] * $network->{'learning rate'};
				$node->{'connectedNodesWest'}->{'weights'}->[$connectedNodeCounter] += $dW;
			}
		}
	}
}



1;

=pod

=head1 NAME

AI::NNFlex::Reinforce - A very simple experimental NN module

=head1 SYNOPSIS

 use AI::NNFlex::Reinforce;

 my $network = AI::NNFlex::Reinforce->new(config parameter=>value);

 $network->add_layer(nodes=>x,activationfunction=>'function');

 $network->init(); 



 use AI::NNFlex::Dataset;

 my $dataset = AI::NNFlex::Dataset->new([
			[INPUTARRAY],[TARGETOUTPUT],
			[INPUTARRAY],[TARGETOUTPUT]]);

 my $sqrError = 10;

 for (1..100)

 {

	 $dataset->learn($network);

 }

 $network->lesion({'nodes'=>PROBABILITY,'connections'=>PROBABILITY});

 $network->dump_state(filename=>'badgers.wts');