THE UNIVERSITY OF BIRMINGHAM
School of Computer Science
THE COGNITION AND AFFECT PROJECT

PAPERS ADDED IN THE YEAR 2018 (APPROXIMATELY)

PAPERS 2018 CONTENTS LIST
MAIN COGAFF INDEX FILE

NOTE

This file is http://www.cs.bham.ac.uk/research/projects/cogaff/16.html
Maintained by Aaron Sloman.
It contains an index to files in the Cognition and Affect Project's Web directory produced or published in the year 2018. Some of the papers published in this period were produced earlier and are included in one of the lists for an earlier period. Some older papers recently digitised may also be included.

Main contents list for the CogAff web site is:
http://www.cs.bham.ac.uk/research/cogaff/0-INDEX.html#contents

A list of PhD and MPhil theses was added in June 2003

This file Last updated: 30 Jul 2018

PAPERS (AND TALKS) IN THE COGNITION AND AFFECT DIRECTORY
Produced or published in 2018 (Approximately)
(Latest first)

The following Contents list (in reverse chronological order) contains links to locations in this file giving further details, including abstracts, and links to the papers themselves.

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CONTENTS -- FILES 2018 (Latest First)

What follows is a list of links to more detailed information about each paper. From there you can select the actual papers, in various formats, e.g. PDF, postscript and some in html.
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DETAILS OF DOCUMENTS AND PRESENTATIONS AVAILABLE

Filename: sloman-ptai17.pdf(PDF)
Title: Huge, Unnoticed, Gaps Between Current AI and Natural Intelligence
Presented at PTAI17 Conference, Univrsity of Leeds, Nov 2017
This is a pre-publication version of the paper to be published by Springer in conference proceedings edited by Vincent Mueller.
Author: Aaron Sloman
Date Installed: 30 Jul 2018

Where published:

To appear in PTAI 2017 Conference proceedings.
Ed. Vincent Mueller, 2018

Abstract:

Despite AI's enormous practical successes, some researchers focus on its potential as science and philosophy: providing answers to ancient questions about what minds are, how they work, how multiple varieties of minds can be produced by biological evolution, including minds at different stages of evolution, and different stages of development in individual organisms. AI cannot yet replicate or faithfully model most of these, including ancient, but still widely used, mathematical discoveries described by Kant as non-empirical, non-logical and non-contingent. Automated geometric theorem provers start from externally provided logical axioms, whereas for ancient mathematicians the axioms in Euclid's Elements were major discoveries, not arbitrary starting points. Human toddlers and other animals spontaneously make similar but simpler topological and geometrical discoveries, and use them in forming intentions and planning or controlling actions. The ancient mathematical discoveries were not results of statistical/probabilistic learning, because, as noted by Kant, they provide non-empirical knowledge of possibilities, impossibilities and necessary connections. Can gaps between natural and artificial reasoning in topology and geometry be bridged if future AI systems use previously unknown forms of information processing machinery -- perhaps "Super-Turing Multi-Membrane" machinery?
Keywords/phrases:
AI as science and philosophy; Can AI model ancient geometers? Can AI model human toddlers? Gaps and limitations of current AI; Super-Turing membrane machines; Replicating mathematical consciousness; Research needed.

For more information about the Meta-Morphogenesis project, see
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html

Date Installed:30 Jul 2018
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NOTE
Older files in this directory (pre 2017) are accessible via the main CogAff index
See also the School of Computer Science Web page.

This file is maintained by
Aaron Sloman
http://www.cs.bham.ac.uk/~axs