'Computing' as Information Compression by Multiple Alignment, Unification and Search

TL;DR

This paper proposes that traditional computing models like Turing Machines can be viewed as processes of information compression through multiple alignment, unification, and search, leading to a new, more versatile computing system.

Contribution

It introduces the ICMAUS framework as a new interpretation of computing operations, suggesting enhancements for a unified, simplified, and more capable computing system.

Findings

ICMAUS offers a new perspective on computing models.

The proposed SP system integrates multiple functions.

Potential for improved pattern recognition and reasoning.

Abstract

This paper argues that the operations of a 'Universal Turing Machine' (UTM) and equivalent mechanisms such as the 'Post Canonical System' (PCS) - which are widely accepted as definitions of the concept of `computing' - may be interpreted as *information compression by multiple alignment, unification and search* (ICMAUS). The motivation for this interpretation is that it suggests ways in which the UTM/PCS model may be augmented in a proposed new computing system designed to exploit the ICMAUS principles as fully as possible. The provision of a relatively sophisticated search mechanism in the proposed 'SP' system appears to open the door to the integration and simplification of a range of functions including unsupervised inductive learning, best-match pattern recognition and information retrieval, probabilistic reasoning, planning and problem solving, and others. Detailed consideration of how the ICMAUS principles may be applied to these functions is outside the scope of this article but relevant sources are cited in this article.