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Alife Digest Number 037
ALIFE LIST: Artificial Life Research List Number 37 Friday, September 7th 1990
ARTIFICIAL LIFE RESEARCH ELECTRONIC MAILING LIST
Maintained by the Indiana University Artificial Life Research Group
Contents:
Crystalization of Complexity
ML91 -- THE EIGHTH INTERNATIONAL WORKSHOP ON MACHINE LEARNING
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From: ashley@spectrum.cs.unsw.OZ.AU (Ashley Aitken)
Subject: Crystalization of Complexity
Date: Wed, 5 Sep 90 16:03:50 AES
G'day A-Lifers,
In my thinkings about the brain, and other physical systems I became more
aware of how the complexity of physical systems seems to crystalize at a
number of different levels. For example, a complete understanding of the
brain seems not to depend on knowledge of the state of every atom bound to
it. The complexity of the brain seems to crystalize out into a number of
levels, the cellular being perhaps one of the lowest and maybe some sort
of symbolic or conceptual levels being amongst the highest.
My question then is, why does the complexity crystalize out so elegantly
like this?
Is it only an approximation and to really know the full function
of the brain, we need to consider all details ?
Is it a necessity of our scientific method ?
Is it a result of evolutionary processes ?
Is it statistically driven ?
It seems that this crystalization doesn't only occur in living systems, it
can be seen in most complex systems. I think if it did not occur then we
would surely be doing a different type of science than we now do and perhaps
we wouldn't even be here to do that science (ie it may be possible to offer
anthropomorphic arguments).
My belief is that it is a result of invariances in the system. For example,
a cell is (or more correctly, some of the properties of a cell are) invariant
under a large number of operations on the atoms of which it is formed. I think
these symmetries make it more likely that one of the invariant configurations
is encountered in evolutionary variations of the system. However, my knowledge
of systems and evolutionary principles is limited. I hope that this is not too
naive a question and answer,
Thanks for an interesting (and diverse) mailing list.
Ooroo,
Ashley Aitken.
--
E-MAIL ashley@spectrum.cs.unsw.oz.au AARNet
ashley%spectrum.cs.unsw.oz@uunet.uu.net Internet
{uunet,ukc,ubc-vision}!munnari!spectrum.cs.unsw.oz!ashley UUCP
POSTAL Academic Address: Residential Address:
School of EE and CS, (Rm 345) c/o Basser College, (Rm 123-4)
University of New South Wales, The Kensington Colleges,
Box 1,PO KENSINGTON,N.S.W.,2033, Box 24,PO KENSINGTON,3033.
AUSTRALIA. AUSTRALIA.
Ph. (02) 697-4419 Fx. (02) 662-2087 Ph. Aust (02) 663-8117
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Date: Fri, 7 Sep 90 10:04:12 CDT
From: Lawrence Birnbaum <birnbaum@fido.ils.nwu.edu>
Subject: ML91 -- THE EIGHTH INTERNATIONAL WORKSHOP ON MACHINE LEARNING
ML91 -- THE EIGHTH INTERNATIONAL WORKSHOP ON MACHINE LEARNING
CALL FOR WORKSHOP PROPOSALS AND PRELIMINARY CALL FOR PAPERS
On behalf of the organizing committee, we are pleased to solicit proposals for
the workshops that will constitute ML91, the Eighth International Workshop on
Machine Learning, to be held in late June, 1991, at Northwestern University,
Evanston, Illinois, USA. We anticipate choosing six workshops to be held in
parallel over the three days of the meeting. Our goal in evaluating workshop
proposals is to ensure high quality and broad coverage of work in machine
learning. Workshop committees -- which will operate for the most part
independently in selecting work to be presented at ML91 -- should include two
to four people, preferably at different institutions. The organizing
committee may select some workshops as proposed, or may suggest changes or
combinations of proposals in order to achieve the goals of quality and
balance.
Proposals are due October 10, 1990, preferably by email to:
ml91@ils.nwu.edu
although hardcopy may also be sent to the following address:
ML91
Northwestern University
The Institute for the Learning Sciences
1890 Maple Avenue
Evanston, IL 60201 USA
fax (708) 491-5258
Please include the following information:
1. Workshop topic
2. Names, addresses, and positions of workshop committee members
3. Brief description of topic
4. Workshop format
5. Justification for workshop, including assessment of breadth of
appeal
Workshop format is somewhat flexible, and may include invited talks, panel
discussions, short presentations, and even small working group meetings.
However, it is expected that the majority of time will be devoted to technical
presentations of 20 to 30 minutes in length, and we encourage the inclusion of
a poster session in each workshop. Each workshop will be allocated
approximately 100 pages in the Proceedings, and papers to be published must
have a minimum length of (most likely) 4 to 5 pages in double column format.
Workshop committee members should be aware of these space limitations in
designing their workshops.
We encourage proposals in all areas of machine learning, including induction,
explanation-based learning, connectionist and neural net models, adaptive
control, pattern recognition, computational models of human learning,
perceptual learning, genetic algorithms, computational approaches to teaching
informed by learning theories, scientific theory formation, etc. Proposals
centered around research problems that can fruitfully be addressed from a
variety of perspectives are particularly welcome.
The workshops to be held at ML91 will be announced towards the end of October.
In the meantime, we would like to announce a preliminary call for papers; the
submission deadline is February 1, 1990. Authors should bear in mind the
space limitations described above.
On behalf of the organizing committee,
Larry Birnbaum
Gregg Collins
Program co-chairs, ML91
(This announcement is being sent/posted to ML-LIST, CONNECTIONISTS, ALife,
PSYCOLOQUY, NEWS.ANNOUNCE.CONFERENCES, COMP.AI, COMP.AI.EDU,
COMP.AI.NEURAL-NETS, COMP.ROBOTICS, and SCI.PSYCHOLOGY. We encourage readers
to forward it to any other relevant mailing list or bulletin board.)
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End of ALife Digest
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