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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

As of 2022, the selection committee for the prize consisted of:[1]

Recipients

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

See also

References

  1. ^ a b "Rumelhart Prize, Cognitive Science Society Official Website". Retrieved July 14, 2022.
  2. ^ 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.
  3. ^ 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.
  4. ^ 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.
  5. ^ 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.
  6. ^ Buchsbaum, Daphna; Bridgers, Sophie; Skolnick Weisberg, Deena; Gopnik, Alison (August 5, 2012). "The power of possibility: causal learning, counterfactual reasoning, and pretend play". Philosophical Transactions of the Royal Society B: Biological Sciences. 367 (1599): 2202–2212. doi:10.1098/rstb.2012.0122. ISSN 0962-8436. PMC 3385687. PMID 22734063.
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