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Cognitive science prize
The David E. Rumelhart Prize for Contributions to the Theoretical Foundations of Human Cognition was founded in 2001 in honor of the cognitive scientist David Rumelhart to introduce the equivalent of a Nobel prize for cognitive science . It is awarded annually to "an individual or collaborative team making a significant contemporary contribution to the theoretical foundations of human cognition".[ 1] The annual award is presented at the Cognitive Science Society meeting, where the recipient gives a lecture and receives a check for $100,000. At the conclusion of the ceremony, the next year's award winner is announced. The award is funded by the Robert J. Glushko and Pamela Samuelson Foundation.
The Rumelhart Prize committee is independent of the Cognitive Science Society. However, the society provides a large and interested audience for the awards.
Selection Committee [ edit ]
As of 2022, the selection committee for the prize consisted of:[ 1]
Year
Recipients
Key contributions
Affiliated institute(s)
2001
Geoffrey E. Hinton
Application of the backpropagation algorithm , Boltzmann machines
University of Toronto ,
Google AI ,
University of California, San Diego ,
Carnegie Mellon University ,
University College London
2002
Richard M. Shiffrin
Atkinson-Shiffrin memory model , Retrieving Effectively From Memory model
Indiana University
2003
Aravind Joshi
Tree-adjoining grammar formalism, Centering Theory
University of Pennsylvania
2004
John Anderson
Adaptive Control of Thought—Rational theory
Carnegie Mellon University ,
Yale University
2005
Paul Smolensky
Integrated Connectionist/Symbolic (ICS) architecture, Optimality Theory , Harmonic Grammar
Johns Hopkins University ,
Microsoft Research ,
University of California, San Diego
2006
Roger Shepard
Non-metric multidimensional scaling , Universal Law of Generalization , theories on mental rotation
Stanford University
2007
Jeffrey L. Elman
TRACE model, Simple Recurrent Neural Network (SRNN)
University of California, San Diego
2008
Shimon Ullman
Theories of motion perception , application of visual routines , saliency maps
Weizmann Institute of Science , Israel ,
Massachusetts Institute of Technology
2009
Susan Carey
Theories of conceptual development and language development , fast mapping
Harvard University ,
Massachusetts Institute of Technology ,
New York University
2010
Jay McClelland
Parallel Distributed Processing , application of connectionist models in cognition
Stanford University ,
Carnegie Mellon University ,
University of California, San Diego
2011
Judea Pearl
The probabilistic approach to artificial intelligence , belief propagation
University of California, Los Angeles ,
Princeton University ,
Electronic Memories, Inc.
2012
Peter Dayan
Application of Bayesian methods to computational neuroscience, Q-learning algorithm, wake-sleep algorithm , Helmholtz machine
Max Planck Institute for Biological Cybernetics ,
University College London ,
Massachusetts Institute of Technology
2013
Linda B. Smith
Dynamic systems approach to cognitive development, early word learning, shape bias
Indiana University
2014
Ray Jackendoff
Conceptual semantics , generative theory of tonal music
Tufts University ,
Brandeis University
2015
Michael I. Jordan
Latent Dirichlet allocation , variational methods for approximate inference , expectation-maximization algorithm
University of California, Berkeley ,
University of California, San Diego ,
Massachusetts Institute of Technology
2016
Dedre Gentner
Structure-Mapping Theory of analogical reasoning , theories of mental models , kind world hypothesis
Northwestern University ,
University of Illinois at Urbana-Champaign ,
Bolt Beranek and Newman, Inc ,
University of Washington
2017
Lila Gleitman
Theories of language acquisition and developmental psycholinguistics , notably the syntactic bootstrapping
University of Pennsylvania
2018
Michael Tanenhaus
Theories of language comprehension, notably the visual world paradigm
University of Rochester ,
Wayne State University
2019
Michelene Chi
Self-explanation, ICAP theory of active learning
Arizona State University ,
2020
Stanislas Dehaene
Theories of numerical cognition , neural basis of reading, neural correlates of consciousness
INSERM , Collège de France
2021
Susan Goldin-Meadow
Innateness of language, gestural systems of communication
University of Chicago
2022
Michael Tomasello
Functional theories of language development , uniqueness of human social cognition, namely the collective intentionality .
Duke University ,
Max Planck Institute for Evolutionary Anthropology ,
University of Leipzig ,
Emory University
2023
Nick Chater
Bayesian Models of Cognition and Reasoning,[ 2] Simplicity theory ,[ 3] 'Now-or-Never' Bottleneck in Language Acquisition[ 4]
University of Warwick ,
University College London ,
University of Edinburgh ,
University of Oxford
2024
Alison Gopnik
Effect of Language on Thought, Development of a Theory of Mind,[ 5] Causal Learning[ 6]
University of California, Berkeley ,
University of Toronto
^ a b "Rumelhart Prize, Cognitive Science Society Official Website" . Retrieved July 14, 2022 .
^ Chater, Nick; Oaksford, Mike; Hahn, Ulrike; Heit, Evan (November 2010). "Bayesian models of cognition" . WIREs Cognitive Science . 1 (6): 811–823. doi :10.1002/wcs.79 . ISSN 1939-5078 .
^ Chater, Nick (April 1999). "The Search for Simplicity: A Fundamental Cognitive Principle?" . The Quarterly Journal of Experimental Psychology Section A . 52 (2): 273–302. doi :10.1080/713755819 . ISSN 0272-4987 .
^ Christiansen, Morten H.; Chater, Nick (January 2016). "The Now-or-Never bottleneck: A fundamental constraint on language" . Behavioral and Brain Sciences . 39 : e62. doi :10.1017/S0140525X1500031X . ISSN 0140-525X .
^ Gopnik, Alison; Meltzoff, Andrew (1998). Words, thoughts, and theories . Learning, development, and conceptual change (2. print ed.). Cambridge, Mass. London: MIT. ISBN 978-0-262-07175-8 .
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