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.

翻译：本文及所附的Python和C++框架是作者认为狭窄(基于歧视)AI.(人工智能)存在问题的产物。 《框架》试图利用一种共同的规章/交换价值(能源),通过潜在的结构表达方式,发展一种通过潜在的结构表达方式的遗传经验的转移,以创造一种模式,使神经结构和所有单元过程都依靠基因和实时信号处理的影响来共同开发;成功的路径由受基因编码形态发展偏见影响的每个时代的峰值分布的稳定性来界定。 这些原则旨在建立一个多样化和强大的网络,通过在模拟中进行培训,将学习转移到规模上的其他媒介,从而能够适应一般任务。