Its nice the networks are now firing and can even demonstrate regionality in firing patterns. However, without a physical body, they are little more than flashing lights. Imagine how useful you would be without a body!

Bodies in DN are very simple right now. Each body comes equipped with two “muscles”. One controls the rotation of the body, affecting orientation and field of view. The other muscle controls thrust, resulting in movement in the direction the body is currently pointing. The simulated environment follows frictionless newtonian physics which means the networks will be learning how to play a simplified game of Asteroids.

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The first synaptic firing test was a complete success. The test bed was a network of 1000 neurons contained in a 50×50x50 cube. Each neuron was connected to 50 other neurons via synapses, resulting in 50,000 synaptic connections. Each cycle of the program executes anywhere from 2ms (0 neurons firing) to 64ms (350 neurons firing, 15,000 synapses activated). 60 cycles were exceuted.

The testbed consisted of four neurotransmitters (A,B,C,D) seeded at random locations in the physical network. Transmitters A and B were given overwhelmingly strong excitory attributes while C and D were given very weak inhibitory attributes. This was done on purpose to test the synaptic connections and make sure my code was functioning. Five neurons were artificially stimulated to start the test.

The test worked wonderfully and even showed some oscillatory behavior, as evidenced by this video (apologies for the quality):

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Neurons, as in the brain, are the base “processing” unit of DN. Unlike most neural networks in existence today, DN’s neurons look like this:

Rather than this:

DN takes the approach of modeling real biological processes. This means the neurons in DN have bodies, axons and dendrites. They are somewhat crude approximations in that they are simplified but they are far more flexible than the current artificial neural nets being used.

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