MESING – a new method of organizing the joint work of neural networks and its metrology

Abstract

A description of a new method for the collective solution of local problems – the method of evolutionary coordination of solutions based on the original use of genetic algorithms – is given. Interaction rules, developed on their basis, coordinate the work of intelligent agents (actors). Based on the Rasch model, an absolute scale for measuring the intellectual power of actors and the costs of intellectual labor when solving local problems with a given probability of their correct solution is introduced. The unit of measurement for these values is introduced and justified – 1 INT. A number of theorems are presented that make it possible to substantiate a new procedure for obtaining a collective solution (mesing) both to increase the intellectual power of a committee of neural networks by 150 times in comparison with a single neural network as part of a committee, and to reduce the probability of an erroneous decision to zero under certain conditions. As a result of the committee’s work, either the correct decision is formed, or the answer “no solution has been found” with a low probability of an erroneous decision.