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arXiv · 2103.15552

Energy Decay Network (EDeN)

Jamie Nicholas Shelley·Optishell Consultancy
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Abstract

This paper and accompanying Python and C++ Framework is the product of the authors perceived problems with narrow (Discrimination based) AI. (Artificial Intelligence) The Framework attempts to develop a genetic transfer of experience through potential structural expressions using a common regulation/exchange value (energy) to create a model whereby neural architecture and all unit processes are co-dependently developed by genetic and real time signal processing influences; successful routes are defined by stability of the spike distribution per epoch which is influenced by genetically encoded morphological development biases.These principles are aimed towards creating a diverse and robust network that is capable of adapting to general tasks by training within a simulation designed for transfer learning to other mediums at scale.

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Jamie Nicholas Shelley, Optishell Consultancy. 2021-03-10. Energy Decay Network (EDeN). https://doi.org/10.31224/osf.io/dfyzn

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