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AIList Digest Volume 5 Issue 143
AIList Digest Monday, 15 Jun 1987 Volume 5 : Issue 143
Today's Topics:
Journal Issues - Neural Networks (IEEE Computer) &
Smolensky on Connectionism (BBS) &
Laming on Sensory Analysis (BBS),
Conference - Genetic Algorithms
----------------------------------------------------------------------
Date: 8 June 1987, 16:25:07 EDT
From: Bruce Shriver <SHRIVER@ibm.com>
Subject: Journal Issue - Neural Networks
Call for Papers and Referees
Special Issue of Computer Magazine
on Neural Networks
The March, 1988 issue of Computer magazine will be devoted
to a wide range of topics in Neural Computing. Manuscripts
that are either tutorial, survey, descriptive, case-study,
applications-oriented or pedagogic in nature are immediately
sought in the following areas:
o Neural Network Architectures
o Electronic and Optical Neurocomputers
o Applications of Neural Networks in Vision, Speech
Recognition and Synthesis, Robotics, Image Process-
ing, and Learning
o Self-Adaptive and Dynamically Reconfigurable Systems
o Neural Network Models
o Neural Algorithms and Models of Computation
o Programming Neural Network Systems
INSTRUCTIONS FOR SUBMITTING MANUSCRIPTS
Manuscripts should be no more than 32-34 typewritten,
double-spaced pages in length including all figures and ref-
erences. No more than 12 references should be cited. Papers
must not have been previously published nor currently sub-
mitted for publication elsewhere. Manuscripts should have a
title page that includes the title of the paper, full name
of its author(s), affiliation(s), complete physical and
electronic address(es), telephone number(s), a 200 word ab-
stract, and a list of keywords that identify the central is-
sues of the manuscript's content.
DEADLINES
o A 200 word abstract on the manuscript is due as soon
as possible.
o Eight (8) copies of the full manuscript is due by
August 30, 1987.
o Notification of acceptance is November 1, 1987.
o Final version of the manuscript is due no later than
December 1, 1987.
SEND SUBMISSIONS AND QUESTIONS TO
Bruce D. Shriver
Editor-in-Chief, Computer
IBM T. J. Watson Research Center
P. O. Box 704
Yorktown Heights, NY 10598
Phone: (914) 789-7626
Electronic Mail Addresses:
arpanet: shriver@ibm.com
bitnet: shriver at yktvmh
compmail+: b.shriver
------------------------------
Date: 5 Jun 87 18:14:46 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Smolensky on Connectionism: BBS Call for Commentators
The following is the abstract of a forthcoming article on which BBS
[Behavioral and Brain Sciences -- An international, interdisciplinary
Journal of Open Peer Commentary, published by Cambridge University Press]
invites self-nominations by potential commentators.
(Please note that the editorial office must exercise selectivity among the
nominations received so as to ensure a strong and balanced cross-specialty
spectrum of eligible commentators. The procedure is explained after
the abstract.)
-----
On the Proper Treatment of Connectionism
Paul Smolensky
Institute of Cognitive Science
University of Colorado
Boulder CO 80309-0430
A set of hypotheses is formulated for a connectionist
approach to cognitive modeling. These hypotheses are
shown to be incompatible with the hypotheses embodied
in traditional cognitive models. The connectionist
models considered are massively parallel numerical com-
putational systems that are a kind of continuous dynam-
ical system. The numerical values in the system
correspond semantically to fine-grained features below
the level of the concepts used to describe the task
domain. The level of analysis is intermediate between
that of symbolic cognitive models and neural models.
The explanations of behavior provided are like those in
traditional physical sciences, unlike the explanations
provided by symbolic models.
Higher-level analyses of these connectionist models
reveal subtle relations to symbolic models. Fundamen-
tally parallel connectionist memory and linguistic
processes are hypothesized to give rise to processes
that are describable at a higher level as sequential
rule application. At the lower level, computation has
the character of massively parallel satisfaction of
numerical constraints; at the higher level this can
lead to competence characterizable by hard rules. Per-
formance will typically deviate from competence since
behavior is achieved not by interpreting hard rules but
by satisfying soft constraints. The result is a picture
in which traditional and connectionist theoretical con-
structs collaborate intimately to provide an under-
standing of cognition.
-----
This is an experiment in using the Net to find eligible commentators
for articles in the Behavioral and Brain Sciences (BBS), an
international, interdisciplinary journal of "open peer commentary,"
published by Cambridge University Press, with its editorial office in
Princeton NJ.
The journal publishes important and controversial interdisciplinary
articles in psychology, neuroscience, behavioral biology, cognitive science,
artificial intelligence, linguistics and philosophy. Articles are
rigorously refereed and, if accepted, are circulated to a large number
of potential commentators around the world in the various specialties
on which the article impinges. Their 1000-word commentaries are then
co-published with the target article as well as the author's response
to each. The commentaries consist of analyses, elaborations,
complementary and supplementary data and theory, criticisms and
cross-specialty syntheses.
[...] Eligible individuals who judge that they
would have a relevant commentary to contribute should contact the editor at
the e-mail address indicated at the bottom of this message, or should
write by normal mail to:
Stevan Harnad
Editor
Behavioral and Brain Sciences
20 Nassau Street, Room 240
Princeton NJ 08542
(phone: 609-921-7771)
Potential commentators should send their names, addresses, a description of
their general qualifications and their basis for seeking to comment on
this target article in particular to the address indicated earlier or
to the following e-mail address:
{seismo, psuvax1, bellcore, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.princeton.edu
[Subscription information is available from Harry Florentine at
Cambridge University Press: 800-221-4512]
[Contact Harnad for further discussion of eligibility, application
procedures, journal circulation, etc. -- KIL]
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 10 Jun 87 04:42:54 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Laming on Sensory Analysis: BBS Multiple Book Review
The following is the abstract of a book that will be multiply reviewed in BBS
[Behavioral and Brain Sciences -- An international, interdisciplinary
Journal of Open Peer Commentary, published by Cambridge University Press].
Self-nominations by potential reviewers/commentators are invited. Please note
that the editorial office must exercise selectivity among the nominations
received so as to ensure a strong and balanced cross-specialty spectrum of
eligible commentators. The procedure is explained after the abstract.
-----
SENSORY ANALYSIS
Donald Laming
Department of Experimental Psychology
University of Cambrdige
Cambridge CB2 3EB ENGLAND
ABSTRACT
Sensory analysis is that initial, preconscious stage of
perception at which features (edges, temporal discon-
tinuities, and periodicities) are picked out from the
random fluctuations that characterize the physical
stimulation of sensory receptors. Sensory analysis may
be studied by means of signal-detection, psychometric-
function and threshold experiments, and my book, SEN-
SORY ANALYSIS, presents a succinct, quasi-quantitative
account of the phenomena revealed thereby. This account
covers all five sensory modalities, emphasizing the
similarities between them.
A succinct account depends on identifying simple prin-
ciples of wide generality, of which the most fundamen-
tal are that (a) sensory discriminations are differen-
tially coupled to the physical stimuli and that (b)
small stimuli are subject to a square-law transform
which makes them less detectable than they would other-
wise be. These two principles are established by com-
parisons between different configurations of two
stimulus levels to be discriminated; they are realized
within a simple physical-analogue model which affords
certain low-level comparisons with neurophysiological
observation. That physical-analogue model consists of a
sequence of elementary operations on the stimulus con-
stituting a stage of sensory processing. The concate-
nation of two of three stages in cascade accommodates
an increased range of experimental phenomena, espe-
cially the detection of sinusoidal gratings.
My BBS precis is organized in three parts: Part I sur-
veys SENSORY ANALYSIS as economically as may be, begin-
ning from the simplest, most fundamental ideas and
working towards phenomena of increasing complexity. A
rather short Part II reviews the most important alter-
native models addressed to some part or other of the
phenomena surveyed. Finally, a very short Part III con-
tributes some metatheoretic remarks on the function of
a theory of sensory discrimination.
Potential commentators/reviewers should send their names, addresses, a
description of their general qualifications and their basis for seeking to
review this book in particular to the following USmail or Email address:
Stevan Harnad, Editor
Behavioral and Brain Sciences
20 Nassau Street, Room 240
Princeton NJ 08542
(phone: 609-921-7771)
{seismo, psuvax1, bellcore, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.princeton.edu
[See previous solicitations in AIList for the full blurb. -- KIL]
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: Fri, 12 Jun 87 15:40:35 edt
From: John Grefenstette <gref@nrl-aic.ARPA>
Subject: Conference - Genetic Algorithms
Second International Conference on
Genetic Algorithms and Their Applications
July 28-31, 1987
MIT
Cambridge, Massachusetts
Sponsored By
American Association for Artificial Intelligence
Naval Research Laboratory
Bolt Beranek and Newman, Inc.
Genetic algorithms are adaptive search techniques based on
principles derived from natural population genetics, and are
currently being applied to a variety of difficult problems in
science, engineering, and artificial intelligence. Topics for
discussion will include:
Fundamental research on genetic algorithms
Machine learning using genetic algorithms
Implementation techniques,
especially on parallel processors
Relationships to connectionism and other
search and learning techniques
Application of genetic algorithms
Conference Committee:
John H. Holland University of Michigan
(Conference Chair)
Lashon B. Booker Navy Center for Applied Research in AI
Dave Davis Bolt Beranek and Newman, Inc.
Kenneth A. De Jong George Mason University
David E. Goldberg University of Alabama
John J. Grefenstette Navy Center for Applied Research in AI
(Program Chair)
Stephen F. Smith Carnegie-Mellon Robotics Institute
Stewart W. Wilson Rowland Institute for Science
(Local Arrangements)
The registration fee is $120 ($175 after June 15) and
includes admission to all sessions, the Conference Proceedings,
a Welcoming Reception, and all coffee breaks and lunches.
The Conference Banquet is $30 additional per person. The
Registration fee for students is $60. For registration forms
and information concerning local arrangements, contact:
Conference Services Office
Room 7-111
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139
(617) 253-1703
For copies of the Conference Proceedings, contact:
Lawrence Erlbaum Associates, Publishers
365 Broadway
Hillsdale, New Jersey 07642
CONFERENCE PROGRAM
TUESDAY, JULY 28, 1987
5:00 - 9:00 REGISTRATION
7:00 - 9:00 WELCOMING RECEPTION
7:00 - 9:00 TUTORIAL (if sufficient interest)
WEDNESDAY, JULY 29, 1987
8:00 REGISTRATION
9:00 OPENING REMARKS
9:20 - 10:40 GENETIC SEARCH THEORY
Finite Markov chain analysis of genetic algorithms
David E. Goldberg and Philip Segrest
An analysis of reproduction and crossover in a
binary-coded genetic algorithm
Clayton L. Bridges and David E. Goldberg
Reducing bias and inefficiency in the selection algorithm
James E. Baker
Altruism in the bucket brigade
Thomas H. Westerdale
10:40 - 11:00 COFFEE BREAK
11:00 - 12:00 ADAPTIVE SEARCH OPERATORS I
Schema recombination in pattern recognition problems
Irene Stadnyk
An adaptive crossover distribution mechanism for
genetic algorithms
J. David Schaffer and Amy Morishima
Genetic algorithms with sharing for multimodal
function optimization
David E. Goldberg and Jon Richardson
12:00 - 2:00 LUNCH
2:00 - 3:20 REPRESENTATION ISSUES
The ARGOT strategy: adaptive representation genetic
optimizer technique
Craig G. Shaefer
Nonstationary function optimization using genetic
algorithms with dominance and diploidy
David E. Goldberg and Robert E. Smith
Genetic operators for high-level knowledge representations
H. J. Antonisse and K. S. Keller
Tree structured rules in genetic algorithms
Arthur S. Bickel and Riva Wenig Bickel
3:20 - 3:40 COFFEE BREAK
3:40 - 5:00 KEYNOTE ADDRESS
Genetic algorithms and classifier systems: foundations
and future directions
John H. Holland
7:00 - 9:00 BUSINESS MEETING
THURSDAY, JULY 30, 1987
9:00 - 10:20 ADAPTIVE SEARCH OPERATORS II
Greedy genetics
G.E. Liepins, M.R. Hilliard, Mark Palmer
and Michael Morrow
Incorporating heuristic information into genetic search
Jung Y. Suh and Dirk Van Gucht
Using reproductive evaluation to improve genetic
search and heuristic discovery
Darrell Whitley
Toward a unified thermodynamic genetic operator
David J. Sirag and Paul T. Weisser
10:20 - 10:40 COFFEE BREAK
10:40 - 12:00 CONNECTIONISM AND PARALLELISM I
Toward the evolution of symbols
Charles P. Dolan and Michael G. Dyer
SUPERGRAN: a connectionist approach to learning,
integrating genetic algorithms and graph induction
Deon G. Oosthuizen
Parallel implementation of genetic algorithms in a
classifier system
George G. Robertson
Punctuated equilibria: a parallel genetic algorithm
J.P. Cohoon, S.U. Hegde, W.N. Martin and D. Richards
12:00 - 2:00 LUNCH
2:00 - 3:20 PARALLELISM II
A parallel genetic algorithm
Chrisila B. Pettey, Michael R. Leuze and John J. Grefenstette
Genetic learning procedures in distributed environments
Adrian V. Sannier II and Erik D. Goodman
Parallelisation of probabilistic sequential search algorithms
Prasanna Jog and Dirk Van Gucht
Parallel genetic algorithms for a hypercube
Reiko Tanese
3:20 - 3:40 COFFEE BREAK
3:40 - 5:00 CREDIT ASSIGNMENT AND LEARNING
Bucket brigade performance: I. Long sequences of classifiers
Rick L. Riolo
Bucket brigade performance: II. Default hierarchies
Rick L. Riolo
Multilevel credit assignment in a genetic learning system
John J. Grefenstette
On using genetic algorithms to search program spaces
Kenneth A. De Jong
6:30 - 10:00 CLAM BAKE
FRIDAY, JULY 31, 1987
9:00 - 10:20 APPLICATIONS I
A genetic system for learning models of consumer choice
David Perry Greene and Stephen F. Smith
A study of permutation crossover operators on the
traveling salesman problem
I.M. Oliver, D.J. Smith and J. R. C. Holland
A classifier based system for discovering scheduling heuristics
M.R. Hilliard, G.E. Liepins, Mark Palmer,
Michael Morrow and Jon Richardson
Using the genetic algorithm to generate LISP source code
to solve the prisoner's dilemma
Cory Fujiko and John Dickinson
10:20 - 10:40 COFFEE BREAK
10:40 - 12:00 APPLICATIONS II
Optimal determination of user-oriented clusters:
an application for the reproductive plan
Vijay V. Raghavan and Brijesh Agarwal
The genetic algorithm and biological development
Stewart W. Wilson
Genetic algorithms and communication link speed design:
theoretical considerations
Lawrence Davis and Susan Coombs
Genetic algorithms and communication link speed design:
constraints and operators
Susan Coombs and Lawrence Davis
12:00 - 2:00 LUNCH
2:00 - 3:20 PANEL DISCUSSION: GA's and AI
3:20 - 3:40 COFFEE BREAK
3:40 - 5:00 INFORMAL DISCUSSION AND FAREWELL
------------------------------
End of AIList Digest
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