COMPUTING AS INFORMATION COMPRESSION


Subject: COMPUTING AS INFORMATION COMPRESSION
From: Gerry Wolff (gerry@sees.bangor.ac.uk)
Date: Tue Jan 18 2000 - 15:31:00 MET


COMPUTING AS INFORMATION COMPRESSION

Two new papers in this research programme have been published
recently:

1 `COMPUTING' AS INFORMATION COMPRESSION BY MULTIPLE ALIGNMENT,
UNIFICATION AND SEARCH is now published in the Journal of Universal
Computer Science 5(11), 777-815, 1999.

The paper may be obtained from http://www.iicm.edu/jucs_5_11 in
Postscript, PDF or HTML formats. If you prefer, I will be happy to send
hard copy (contact details below).

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). In this context, 'multiple
alignment' has a meaning which is similar to but distinct from its
meaning in bio-informatics, while 'unification' means a simple merging
of matching patterns, a meaning which is related to but simpler than
the meaning of that term in logic.

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 the article.

2 PROBABILISTIC REASONING AS INFORMATION COMPRESSION BY MULTIPLE
ALIGNMENT, UNIFICATION AND SEARCH: AN INTRODUCTION AND OVERVIEW is now
published in the Journal of Universal Computer Science 5(7), 418-462,
1999.

The paper may be obtained from http://www.iicm.edu/jucs_5_7 in
Postscript, PDF or HTML formats. As with the other paper, I will be
happy to send hard copy if you prefer.

This article introduces the idea that probabilistic reasoning (PR) may
be understood as ICMAUS.

A software model, SP61, has been developed for the discovery and
formation of `good' multiple alignments, evaluated in terms of
information compression. The model is described in outline.

Using examples from the SP61 model, this article describes in outline
how the ICMAUS framework can model various kinds of PR including: PR in
best-match pattern recognition and information retrieval; one-step
`deductive' and `abductive' PR; inheritance of attributes in a class
hierarchy; chains of reasoning (probabilistic decision networks and
decision trees, and PR with `rules'); geometric analogy problems;
nonmonotonic reasoning and reasoning with default values; modelling the
function of a Bayesian network.

A description of the whole programme of research and copies of other
articles may be found at
http://www.sees.bangor.ac.uk/~gerry/sp_summary.html.

Gerry Wolff

Dr J G Wolff, School of Informatics, University of Wales, Dean Street,
Bangor, Gwynedd, LL57 1UT, UK. Tel: +44 1248 382691. Fax: +44 1248
361429. E-mail: gerry@sees.bangor.ac.uk Web:
http://www.sees.bangor.ac.uk/~gerry/

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