On Eco-Grammar Systems and Artificial Neural Networks

Abstract

Eco-grammar systems and artificial neural networks have many common features: massive parallelism, independently working elements (agents/neurons), cooperation of the elements and, not least, universal computational power (at least as that of Turing machine).
We prove the possibility to simulate each step of a system of one of the types by a fixed number of steps of a system of the other type without loss of parallelism. Moreover, the number of processing elements (neurons, agents) of the model is a function of class O (n), where n is a number of processing elements of the original system.