Exploiting Natural Asynchrony and Local Knowledge

Bio-inspired processes are involved more and more in today’s technologies, yet their modelling and implementation tend to be taken away from their original concept because of the limitations of the classical computation paradigm.

To address this, we previously introduced systemic computation (SC), a model of interacting systems with natural characteristics, and further introduced a modeling platform with a bio-inspired system implementation. In this paper, we investigate the impact of local knowledge and asynchronous computation: significant natural properties of biological neural networks (NN) and naturally handled by SC. We present here a bio-inspired model of artificial NN, focussing on agent interactions, and show that exploiting these built-in properties, which come for free, enables neural structure flexibility without reducing performance.

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Exploiting Natural Asynchrony and Local Knowledge within Systemic Computation to Enable Generic Neural Structures.
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