A Quantification Approach for Transferability in Lifelike Computing Systems

TL;DR

This paper introduces a new metric for quantifying transferability in lifelike computing systems, enabling dynamic assessment of system behavior and controllability during runtime.

Contribution

It proposes the first metric specifically designed to measure transferability in lifelike systems, addressing the challenge of maintaining control amid high autonomy.

Findings

The metric effectively describes system behavior at runtime.

Example applications demonstrate the metric's applicability.

The approach supports dynamic quantification of lifelike properties.

Abstract

The basic idea of lifelike computing systems is the transfer of concepts in living systems to technical use that goes even beyond existing concepts of self-adaptation and self-organisation (SASO). As a result, these systems become even more autonomous and changeable - up to a runtime transfer of the actual target function. Maintaining controllability requires a complete and dynamic (self-)quantification of the system behaviour with regard to aspects of SASO but also, in particular, lifelike properties. In this article, we discuss possible approaches for such metrics and establish a first metric for transferability. We analyse the behaviour of the metric using example applications and show that it is suitable for describing the system's behaviour at runtime.