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

PAPERS ADDED IN THE YEAR 2012 (APPROXIMATELY)

PAPERS 2012 CONTENTS LIST
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NOTE

This file is http://www.cs.bham.ac.uk/research/projects/cogaff/12.html
Maintained by Aaron Sloman -- who does not respond to Facebook requests.
It contains an index to files in the Cognition and Affect Project's Web directory
produced or published in the year 2012. 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: 22 Apr 2012; 2 Jun 2012; 20 Dec 2012; 9 Mar 2013;12 Dec 2013; 13 Mar 2014


PAPERS (AND TALKS) IN THE COGNITION AND AFFECT DIRECTORY
Produced or published in 2012 (Approximately)
(Latest first)

Most of the papers listed here are in postscript and PDF format. More recent papers are in PDF only.
For information on free browsers for these formats see http://www.cs.bham.ac.uk/~axs/browsers.html


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.

JUMP TO DETAILED LIST (After Contents)

CONTENTS -- FILES 2012 (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.


DETAILS OF FILES AVAILABLE


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Filename: chappell-demery-arriola-sloman-2012.pdf (PDF)
Title: How to build an information gathering and processing system:
      Lessons from naturally and artificially intelligent systems

Authors: Jackie Chappell, Zoe P. Demery, Veronica Arriola-Rios, Aaron Sloman
University of Birmingham.
Date Installed: 2 Nov 2013

Where published:
In Behavioural Processes 89 (2012) 179-186 doi:10.1016/j.beproc.2011.10.001

Abstract:

Imagine a situation in which you had to design a physical agent that could
collect information from its environment, then store and process that information
to help it respond appropriately to novel situations. What kinds of information
should it attend to? How should the information be represented so as to allow
efficient use and re-use? What kinds of constraints and trade-offs would there
be? There are no unique answers. In this paper, we discuss some of the ways in
which the need to be able to address problems of varying kinds and complexity can
be met by different information processing systems. We also discuss different
ways in which relevant information can be obtained, and how different kinds of
information can be processed and used, by both biological organisms and
artificial agents. We analyse several constraints and design features, and show
how they relate both to biological organisms, and to lessons that can be learned
from building artificial systems. Our standpoint overlaps with Karmiloff-Smith
(1992) in that we assume that a collection of mechanisms geared to learning and
developing in biological environments are available in forms that constrain, but
do not determine, what can or will be learnt by individuals.
Keywords: exploration; play; information processing; learning;


This version updated after book publication: March 2014
Filename: sloman-on-schmidhuber.pdf (PDF)
Filename: sloman-on-schmidhuber.html (HTML)
Title:

Chapter 4A. Aaron Sloman on Schmidhuber's "New Millennium AI and the Convergence of History 2012"

Commentary on Chapter 4: New Millennium AI and the Convergence of History: Update of 2012
By Jürgen Schmidhuber
Included in the volume mentioned below. Available online here:
https://docs.google.com/file/d/0BwK0OPe_m9QNbW4yUldmREx1VGs/edit?pli=1

Author: Aaron Sloman
Date Installed: 16 Dec 2012

Where published:

In The Singularity Hypotheses: A Scientific and Philosophical Assessment
Eds. Amnon H. Eden, James H. Moor, Johnny H. Soraker and Eric Steinhart, pp 79--80.
Springer-Verlag. Berlin, Heidelberg The Frontiers Collection 2013
Table of contents and some online chapters

Abstract (extracts from short article):

.....
I have problems both with the style and the content of this paper,....
.....
I do not doubt that the combination of technical advances by the author and increases
in computer power have made possible new impressive demonstrations including
out-performing rival systems on various benchmark tests.

However, it is not clear to me that those tests have much to do with animal or human
intelligence or that there is any reason to believe this work will help to bridge the
enormous gaps between current machine competences and the competences of squirrels,
nest-building birds, elephants, hunting mammals, apes, and human toddlers.
.....


(Moved to another file: 25 Sep 2015)
What are the purposes of vision?


Moved to another file: http://www.cs.bham.ac.uk/research/projects/cogaff/62-80.html#1980-01
Title: What kind of indirect process is visual perception? (BBS 1980)


Filename:sloman-ecai-anniv.pdf
Title: Biological, computational and robotic connections with Kant's theory of mathematical knowledge

Author: Aaron Sloman

Date Installed: 4 Sep 2012 (Presented 29 Aug 2012)
Last Updated: 6 Dec 2012; 13 Apr 2013; 23 Oct 2013; 27 Mar 2014 (May be expanded later)

Where published:

This is a freely available, version of an invited paper for the
"Turing and Anniversary Session" at ECAI2012, in Montpellier
http://www2.lirmm.fr/ecai2012/.
PDF slides for the conference presentation are here:
http://www.cs.bham.ac.uk/research/projects/cogaff/talks/#anniv
A version of this paper also appeared in a special issue of the journal AI Communications
http://iospress.metapress.com/content/e6q55458wv004312/?p=053f5df8b817437d83c68cda2aa80c6f&pi=6
The freely available online version here will be modified from time to time, and will have
more references to related work (the journal version is space-restricted).
I am not able to write an authoritative overview of the history of any portion of AI,
or European AI, so this is merely a personal account of some problems that got me
into AI around 1971, but which I think have not yet been addressed adequately.
This version will go on being revised in response to comments, criticisms,
suggestions and afterthoughts, like most of my publications.

Closely related web pages

Abstract:

In my research I meander through various disciplines, using fragments of AI that I regard as relevant, willing to learn from anyone whose ideas contribute. This makes me unfit to write the history of European collaboration on some area of AI research as originally intended for the ECAI event and special issue of the Journal AI Communications. However, by interpreting the topic rather loosely, I can regard some European philosophers who were interested in Philosophy of mathematics as early AI researchers from whom I learnt much, such as Kant and Frege. Hume's work is also relevant. Moreover, more recent work by Annette Karmiloff-Smith, begun in Geneva with Piaget then developed independently, helps to identify important challenges for AI (and theoretical neuroscience), that also connect with philosophy of mathematics and the future, rather than the history, of robotics. So this paper presents an idiosyncratic survey of a subset of AI stretching back in time, and deep into other disciplines, including philosophy, psychology and biology, and possibly also deep into the future.

Keywords:
Kant, Frege, Mathematics, Representational-Redescription, Empirical knowledge,
Necessary truths, Geometry, Robots


Filename: sloman-computational-mind.pdf (PDF)
Title: Towards a Computational Theory of Mind

Originally in Artificial Intelligence - Human Effects, (Eds) M. Yazdani and A. Narayanan,
Ellis Horwood, Chichester, 1984. pp 173--182
Author: Aaron Sloman
Date: Originally published 1984. Added here 7 Aug 2012, with an End Note about related work.

Abstract:

(From the introduction to the chapter.)
Cognitive Science has three interrelated aspects: theoretical, applied and
empirical. Work in all three areas depends on and feeds back into the other two.
Theoretical work explores possible computational systems, possible mental
processes and structures, attempting to understand what sorts of mechanisms and
representational systems are possible, how they differ, what their strengths and
weaknesses are, etc. Empirical work studies existing intelligent systems, e.g.
humans and other animals. Applied work is both concerned with problems relating
to existing minds (e.g. learning difficulties, psychopathology) and also the
design of new useful computational systems. This paper sketches some of the
assumptions underlying much of the theoretical work, and hints at some of the
practical applications. In particular, education and psychotherapy are both
activities in which the computational processes in the mind of the pupil or
patient are altered. In order to understand what they are doing, educationalists
and psychotherapists require a computational theory of mind.
This is not the dehumanising notion it may at first appear to be.

Filename: sloman-3cgi-2012-final.pdf
Title: Meta-morphogenesis and the Creativity of Evolution

Final (shortened) version of paper for proceedings of ECAI 2012 Workshop on
Computational Creativity, Concept Invention, and General Intelligence,

Longer (unpublished) version below ( work in progress: likely to be further expanded).
This is part of the Meta-Morphogenesis project: http://tinyurl.com/M-M-Gen

Author: Aaron Sloman
Date Installed: 30 Jun 2012; updated 16 Jul 2012; 20 Dec 2012 (Better structured)

Abstract:

Whether the mechanisms proposed by Darwin and others suffice to explain the
achievements of biological evolution remains open. One problem is the difficulty
of knowing exactly what needs to be explained. Evolution of information-processing
capabilities and supporting mechanisms is much harder to detect than evolution of
physical form, and physical behaviours in part because much goes on inside the
organism, and in part because it often has abstract forms whose physical
manifestations do not enable us to identify the abstractions easily. Moreover, we
may not yet have the concepts required for looking at or thinking about the right
things. AI should collaborate with other disciplines in attempting to identify
the many important transitions in information processing capabilities, ontologies,
forms of representation, mechanisms and architectures that have occurred in
biological evolution, in individual development (epigenesis) and in social/cultural
evolution - including processes that can modify later forms of evolution and
development: meta- morphogenesis.

Conjecture: The cumulative effects of successive phases of meta-morphogenesis
produce enormous diversity among living information processors, explaining how
evolution came to be the most creative process on the planet.

Keywords:
Architecture, biological information-processing, computation, developmental
affordance, evolutionary affordance, learning, morphogenesis, meta-morphogenesis,
ontologies, representation, representational redescription, toddler-theorems.


Filename: sloman-3cgi-2012.pdf
Title: Meta-morphogenesis and the Creativity of Evolution (EXPANDED VERSION installed 20 Dec 2012)
(Work in progress: may change.)

Part of the Meta-Morphogenesis project: http://tinyurl.com/M-M-Gen
Author: Aaron Sloman
Date Installed: 16 Jul 2012

Where published:

This is an expanded version of paper for ECAI 2012 Workshop on
``Computational Creativity, Concept Invention, and General Intelligence'',
Monday 27th August 2012, Montpellier.
http://www.cogsci.uni-osnabrueck.de/~c3gi
NOTE: the published version had to be shorter than this version. See above.

Abstract:

Whether the mechanisms proposed by Darwin and others suffice to explain the
achievements of biological evolution remains open. Variation in heritable features
can occur spontaneously, and Darwinian natural selection can explain why some new
variants survive longer than others. But that does not satisfy Darwin's critics and
also worries supporters who understand combinatorial search spaces. One problem is
the difficulty of knowing exactly what needs to be explained: Most research has
focused on evolution of physical form, and physical competences and behaviours, in
part because those are observable features of organisms. What is much harder to
observe is evolution of information-processing capabilities and supporting mechanisms
(architectures, forms of representation, algorithms, etc.). Information-processing in
organisms is mostly invisible, in part because it goes on inside the organism, and in
part because it often has abstract forms whose physical manifestations do not enable
us to identify the abstractions easily. Compare the difficulty of inferring thoughts,
percepts or motives from brain measurements, or decompiling computer instruction
traces. Moreover, we may not yet have the concepts required for looking at or
thinking about the right things: we may need more than the vast expansion of our
conceptual tools for thinking about information processing capabilities and
mechanisms in the last half century. However, while continually learning what to look
for, we can collaborate in attempting to identify the many important transitions in
information processing capabilities, ontologies, forms of representation, mechanisms
and architectures that have occurred on various time-scales in biological evolution,
in individual development (epigenesis) and in social/cultural evolution - including
processes that can modify later forms of evolution and development:
meta-morphogenesis. Conjecture: The cumulative effects of successive phases of
meta-morphogenesis produce enormous diversity among living information processors,
explaining how evolution came to be the most creative process on the planet. Progress
in AI depends on understanding the products of this process.

Keywords:

Architecture, biological information-processing, computation, developmental
affordance, evolutionary affordance, learning, morphogenesis, meta-morphogenesis,
ontologies, representation, representational redescription, toddler-theorems.

Filename: sloman-jmc-aisb.html(Added Aug 2016)
Filename: sloman-jmc-aisb.pdf
Title: John McCarthy - Some Reminiscences

Author: Aaron Sloman
Date Installed: 8 Dec 2011; Updated 2 Jun 2012; 6 Jun 2012; 1 Aug 2016

Where published:

A personal memoir, published in the AISB Quarterly, no 133, January 2012, pp 7-10.
This is an expanded version of a pre-publication draft, including some afterthoughts.
See also The AISB Quarterly Archive

Updated 25 Sep 2015:
I've found an excellent online video interview: John McCarthy talking to Jeffrey Mishlove:
https://www.youtube.com/watch?v=Ozipf13jRr4

Abstract:

[Extract from opening paragraphs]
John McCarthy died aged 84 on 24th October 2011. Since then, much has been written
about his life and work (e.g. search for his name and "homage", or "obituary"), and
no doubt there will be much more. I shall not attempt to emulate or compete with any
of the formal obituaries. Instead, I'll offer a few personal recollections and
reflections.

There is also much to read on his web site, since he was one of the people who led the way
in making everything he wrote freely available to all. It was from him that I learnt
to cross out any part of a publisher's copyright agreement that restricted my right
to post versions of my papers on my web site. Only one publisher has ever objected
(so I withdrew the paper).

One of the most important events in my academic life occurred when Max Clowes, then the
leading AI researcher at Sussex university, introduced me to AI, allowed me to attend
his programming tutorials, and gave me things to read, by Simon, Newell, Minsky, McCarthy
and others. It quickly became clear that AI was very relevant to old philosophical
problems, especially in the papers I read by Minsky and McCarthy.

One day Max suggested that I should read the 1969 paper by McCarthy and Hayes,
and lent me his copy.

I found it very interesting, especially the distinction between metaphysical,
epistemological and heuristic adequacy of forms of representation of the world
(echoing, but different from, the three kinds of adequacy in (Chomsky, 1965)). ....


Title: An Overview Of Some Unsolved Problems In Artificial Intelligence
Moved to another file. (29 Sep 2015)


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