Toward a formal theory for computing machines made out of whatever physics offers: extended version

TL;DR

This paper advocates for a new formal theory called 'fluent computing' to guide the design of unconventional physical computing systems, emphasizing bottom-up modeling based on measurable physical effects rather than symbolic reasoning.

Contribution

It introduces 'fluent computing', a novel bottom-up theoretical framework for physical computing systems inspired by physics, contrasting with traditional symbolic models.

Findings

Proposes a formal strategy for unconventional computing

Defines 'fluent computing' as a bottom-up modeling approach

Highlights the importance of measurable physical effects in computing

Abstract

Approaching limitations of digital computing technologies have spurred research in neuromorphic and other unconventional approaches to computing. Here we argue that if we want to systematically engineer computing systems that are based on unconventional physical effects, we need guidance from a formal theory that is different from the symbolic-algorithmic theory of today's computer science textbooks. We propose a general strategy for developing such a theory, and within that general view, a specific approach that we call "fluent computing". In contrast to Turing, who modeled computing processes from a top-down perspective as symbolic reasoning, we adopt the scientific paradigm of physics and model physical computing systems bottom-up by formalizing what can ultimately be measured in any physical substrate. This leads to an understanding of computing as the structuring of processes, while classical models of computing systems describe the processing of structures.