Deciding Networks of Evolutionary Processors

Abstract

In this paper we discuss the usage of Accepting Networks of Evolutionary Processors (ANEPs for short) as deciding devices. In this context we define a new halting condition for this model, which seems more coherent with the rest of the theory than the previous such definition, and show that all the computability results reported so far remain valid in the new framework. Moreover, we give a direct and efficient simulation of an arbitrary ANEP by a complete ANEP, thus, showing that the efficiency of deciding a language by ANEPs is not influenced by the network's topology. Finally, we obtain a surprising characterization of P NP[log] as the class of languages that can be decided in polynomial time by ANEPs.

On Turing Machines Deciding According to the Shortest Computations

“…Moreover, from a theoretical point of view, considering such halting conditions could lead to novel characterizations of a series of complexity classes (like the ones discussed in this paper) by means of nature-inspired computational models, as they seem quite close to the idea of deciding with respect to the shortest computations. To this end, we refer to the papers [11,12], and we leave open the question of whether similar results could be obtained for bio-inspired machines with more particular and compact structure [13][14][15] or for bio-inspired problem solvers [16].…”