Richard M. Shiffrin awarded the Rumelhart Prize

[Cognitive Science Society]

Richard M. Shiffrin Chosen to Receive the David E. Rumelhart Prize
for Contributions to the Formal Analysis of Human Cognition

The Glushko-Samuelson Foundation and the Cognitive Science Society are
pleased to announce that Richard M. Shiffrin has been chosen as the
second recipient of the $100,000 David E. Rumelhart Prize, awarded
annually for an outstanding contribution to the formal analysis of
human cognition. Shiffrin will receive this prize and give the Prize
Lecture at the 2002 Meeting of the Cognitive Science Society, at
George Mason University, August 7-11, 2002.

Shiffrin has made many contributions to the modeling of human
cognition in areas ranging from perception to attention to learning,
but is best known for his long-standing efforts to develop explicit
models of human memory. His most recent models use Bayesian, adaptive
approaches, building on previous work but extending it in a critical
new manner, and carrying his theory beyond explicit memory to implicit
learning and memory processes. The theory has been evolving for about
35 years, and as a result represents a progression similar to the best
theories seen in any branch of science.

Shiffrin's major effort began in 1968, in a chapter with Atkinson [1]
that laid out a model of the components of short- and long-term memory
and described the processes that control the operations of memory.
The Atkinson-Shiffrin model encapsulated empirical and theoretical
results from a very large number of publications that modeled
quantitatively the relation of short- to long-term memory. It
achieved its greatest success by showing the critical importance---and
the possibility---of modeling the control processes of cognition.
This chapter remains one of the most cited works in the entire field
of psychology.

Shiffrin's formal theory was taken forward in a quantum leap in 1980
[2] and 1981 [3] with the SAM (Search of Associative Memory) model.
This was a joint effort with Jeroen Raaijmakers, then a graduate
student. The SAM model quantified the nature of retrieval from
long-term memory, and characterized reCALL as a memory search with
cycles of sampling and recovery. The SAM theory precisely
incorporates the notions of interactive cue combination that are now
seen to lie at the heart of memory retrieval. Another major quantum
step occurred in 1984 [4] when the theory was extended to recognition
memory. With another former student, Gary Gillund, Shiffrin initiated
what has become the standard approach to recognition memory, in which
a decision is based on summed activation of related memory traces. It
was a major accomplishment that the same retrieval activations that
had been used in the recall model could be carried forward and used to
predict a wide range of recognition phenomena. The next major step
occurred in 1990, when Shiffrin published two articles on the
list-length effect with his student Steve Clark and his colleague,
Roger Ratcliff [5, 6]. This research was of critical importance in
that it established clearly that experience leads to the
differentiation, rather than the mere stregthening, of the
representations of items in memory.

In 1997, the theory evolved in a radical direction in an important
paper with another former student, Mark Steyvers [7]. Although the
changes were fundamental, the new model retained the best concepts of
its predecessors, so that the previous successful predictions were
also a part of the new theory. REM added featural representations, to
capture similarity relations among items in memory. Building on
earlier ideas by John Anderson, and related ideas developed in
parallel by McClelland and Chappell, Shiffrin used Bayesian principles
of adaptive and optimal decision making under constraints to guide the
selection of the quantitative form of the activation functions. In
addition, storage principles were set forth that provided mechanisms
by which episodic experience could coalesce over development and
experience into permanent non-contextualized knowledge. This latter
development allowed the modeling of implicit memory phenomena, in work
that is just now starting to appear in many journals, including a
theory of long-term priming [with Schooler and Raaijmakers, 8] and a
theory of short-term priming [with his student David Huber and others,
9]. The short-term priming research showed that the direction of
priming can be reversed by extra study given to particular primes,
leading to another conceptual breakthrough. A new version of the REM
model explains this and other findings by assuming that some prime
features are confused with test item features, and that the system
attempts to deal with this situation optimally by appropriate
discounting of evidence from certain features.

Biographical Information
Shiffrin received his Ph. D. from the Mathematical Psychology Program
in the Department of Psychology at Stanford University in 1968, the
year after Rumelhart received his degree from the same program. Since
1968 he has been on the faculty of the Department of Psychology at
Indiana University, where he is now the Luther Dana Waterman Professor
of Psychology and Director of the Cognitive Science Program. Shiffrin
has accumulated many honors, including membership in the National
Academy of Sciences, the American Academy of Arts and Sciences, the
Howard Crosby Warren Award of the Society of Experimental
Psychologists, and a MERIT Award from the National Institute of Mental
Health. Shiffrin has served the field as editor of the Journal of
Experimental Psychology: Learning Memory and Cognition, and as a
member of the governing boards of several scientific societies.

Cited Articles By Richard M. Shiffrin

[1] Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A
proposed system and its control processes. In K. W. Spence and
J. T. Spence (Eds.), The Psychology of Learning and Motivation:
Advances in Research and Theory (Vol. 2, pp. 89-195). New York:
Aaademic Press.

[2] Raaijmakers, J. G. W., & Shiffrin, R. M. (1980). SAM: A theory of
probabilistic search of associative memory. In Bower, G. H. (Ed.),
The Psychology of Learning and Motivation, Vol. 14, 207-262. New
York: Academic Press.

[3] Raaijmakers, J. G. W., & Shiffrin, R. M. (1981). Search of
associative memory. Psychological Review, 88, 93-134.

[4] Gillund, G., & Shiffrin, R. M. (1984). A retrieval model for both
recognition and recall. Psychological Reviw, 91, 1-67.

[5] Ratcliff, R., Clark, S., & Shiffrin, R. M. (1990). The
list-strength effect: I. Data and discussion. Journal of
Experimental Psychology: Learning, Memory, and Cognition, 16, 163-178.

[6] Shiffrin, R. M., Ratcliff, R., & Clark, S. (1990). The
list-strength effect: II. Theoretical mechanisms. Journal of
Experimental Psychology: Learning, Memory, and Cognition, 16, 179-195.

[7] Shiffrin, R. M., & Steyvers, M. (1997). A model for recognition
memory: REM: Retrieving effectively from memory. Psychonomic Bulletin
and Review, 4 (2), 145-166.

[8] Schooler, L., Shiffrin, R. M., & Raaijmakers, J. G. W. (2001). A
model for implicit effects in perceptual identification. Psychological
Review, 108, 257-272.

[9] Huber, D. E., Shiffrin, R. M., Lyle, K. B., & Ruys, K. I. (2001).
Perception and preference in short-term word priming. Psychological
Review, 108, 149-182.


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Geoffrey E. Hinton Named First Recipient of the David E. Rumelhart Prize

May 3, 2001

Today the Glushko-Samuelson foundation and the Cognitive Science
Society jointly announced that Geoffrey E. Hinton has been named the first
recipient of the David E. Rumelhart Prize for contemporary
contributions to the formal analysis of human cognition. Hinton, the
Director of the Gatsby Computational Neuroscience Unit at University
College, London, was chosen from a large field of outstanding nominees
because of his seminal contributions to the understanding of neural
networks.

"Hinton's insights into the analysis of neural networks played a
central role in launching the field in the mid-1980's" said Professor
James McClelland of Carnegie Mellon University, Chair of the Prize
Selection Committee, "Geoff also played a major role in conveying the
relevance of neural networks to higher-level cognition." Professor
Lawrence Barsalou of Emory University, President of the Cognitive
Science Society, agreed with this assessment. "Hinton's contributions
to Cognitive Science have been pivotal", said Barsalou. "As the first
recipient he sets a great example for future awards." Hinton will
receive the prize, which includes a monetary award of $100,000, at the
annual meeting of the Society in Edinburgh, Scotland, in early August,
2001.

The Rumelhart prize acknowledges intellectual generosity and effective
mentoring as well as scientific insight. "Dave Rumelhart gave away
many scientific ideas, and made important contributions to the work of
many of his students and co-workers" said Robert J. Glushko, President of
the Glushko-Samuelson foundation. He added "Hinton stands out not
only for his own contributions but for his exemplary record in
mentoring young scientists." A total of eighteen graduate students
have received their Ph. D.'s under Hinton's supervision.
In conjunction with naming Hinton as the first recipient of the David
E. Rumelhart Prize, the Glushko-Samuelson foundation announced that
the prize will be awarded on an annual basis, instead of biennially.
"This change reflects the number of outstanding scientists who were
nominated for the award" noted Glushko. "I am pleased that my
foundation can play a role in honoring their contributions to
cognitive science." The second recipient of the Prize will be
announced at the Edinburgh meeting of the society, and will give the
prize lecture at the next annual meeting, which will be at George
Mason University in August, 2002.

For further information, please visit the David E. Rumelhart Prize
web site:
http://www.cnbc.cmu.edu/derprize/DerPrize2001.html
or contact:
Robert J. Glushko, 415-644-8731
James L. McClelland, 412-268-3157



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Cognitive Science Society
c/o Tanikqua Young
Department of Psychology
University of Texas
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Phone: (512) 471-2030
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