flow networks

Flow networks are graphs where energy can transmit around the graph. In this project graph edges have weights giving a capacity or resistance value to transfer energy form the source neuron to the sink neuron.

Flow networks are interesting because even with a small networks (n=3, in a DCG), you can get chaotic, unpredictable behaviors.

Flow networks are the key to this project`s AI. Even with 10 neurons in a DCG has quadriillion different (unique, nonisomorphic) configurations, not including the current energy value at any given neuron. A graph essentially encodes a concept (endeme from wikiwikiweb?) and it doesn't take much to encode many different such concepts.

One a graph configuration becomes stable (in this project that means repeats = 2), a new "meta" neuron (with a name placed by the teacher, should they get wise to what the graph represents) is created.