File:   examples/ex_aln.pl
        Author: Josiah Bryan, jdb@wcoil.com
        Desc:
        
        This is a simple example of a _basic_ ALN implementation in
        under 210 lines of code. In this demo we make use of the 
        custom node connector as described in the POD. We also 
        insert our own method over the node's internal adjust_weight()
        method to make ALN learning a bit easire. This demo also adds
        a temporary method to the network to print the logical type of 
        each node, called print_aln();

        print_aln() prints simple diagram of the
        network similar to this (this is for a $net=Tree(8,1) with 
        $net->learn([1,1,0,1,0,1,1,1],[0]), and each line represents 
        a layer):
        
        L R L L L L L L
        OR OR OR OR
        OR OR
        AND
        
        All the standard methods that work on AI::NeuralNet::Mesh work
        on the object returned by Tree(). load() and save() will correctly
        preserve the gate structure and types of your network. learn_set()
        and everything else works pretty much as expected. Only thing
        that is useless is the crunch() method, as this only takes binary
        inputs. But...for those of you who couldnt live without integers
        in your network...I'm going to create a small package in the next 
        week, AI::NeuralNet::ALNTree, from this code. It will which includes 
        a integer-vectorizer (convert your integers into bit vectors), a bit 
        vector class to play with, as well as support for concating and 
        learning bit vectors. But, for now, enjoy this!
        
        This file contains just a simple, functional, ALN implementation. 
                                
                                                                Enjoy!