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.
As of 2022, the selection committee for the prize consisted of:
| Year | Recipients | Key contributions | Affiliated institute(s) | |
|---|---|---|---|---|
| 2001 | Application of the backpropagation algorithm, Boltzmann machines | University of Toronto,Google AI, University of California, San Diego, University College London | ||
| 2002 | Atkinson-Shiffrin memory model, Retrieving Effectively From Memory model | Indiana University | ||
| 2003 | Tree-adjoining grammar formalism, Centering Theory | University of Pennsylvania | ||
| 2004 | Adaptive Control of Thought—Rational theory | Carnegie Mellon University, Yale University | ||
| 2005 | Integrated Connectionist/Symbolic (ICS) architecture, Optimality Theory, Harmonic Grammar | Johns Hopkins University, Microsoft Research, | ||
| 2006 | Non-metric multidimensional scaling, Universal Law of Generalization, theories on mental rotation | Stanford University | ||
| 2007 | TRACE model, Simple Recurrent Neural Network (SRNN) | University of California, San Diego | ||
| 2008 | Theories of motion perception, application of visual routines, saliency maps | Weizmann Institute of Science, Israel, Massachusetts Institute of Technology | ||
| 2009 | Theories of conceptual development and language development, fast mapping | Harvard University, Massachusetts Institute of Technology, | ||
| 2010 | Parallel Distributed Processing, application of connectionist models in cognition | Stanford University, | ||
| 2011 | The probabilistic approach to artificial intelligence, belief propagation | University of California, Los Angeles, Princeton University, Electronic Memories, Inc. | ||
| 2012 | Max Planck Institute for Biological Cybernetics, University College London, Massachusetts Institute of Technology | |||
| 2013 | Dynamic systems approach to cognitive development, early word learning, shape bias | Indiana University | ||
| 2014 | Conceptual semantics, generative theory of tonal music | Tufts University, Brandeis University | ||
| 2015 | 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 | Structure-Mapping Theory of analogical reasoning, theories of mental models, kind world hypothesis | Northwestern University, University of Illinois at Urbana-Champaign, | ||
| 2017 | Theories of language acquisition and developmental psycholinguistics, notably the syntactic bootstrapping | University of Pennsylvania | ||
| 2018 | Theories of language comprehension, notably the visual world paradigm | University of Rochester, Wayne State University | ||
| 2019 | Self-explanation, ICAP theory of active learning | Arizona State University, | ||
| 2020 | Theories of numerical cognition, neural basis of reading, neural correlates of consciousness | INSERM, Collège de France | ||
| 2021 | Innateness of language, gestural systems of communication | University of Chicago | ||
| 2022 | Functional theories of language development, uniqueness of human social cognition, namely the collective intentionality. | Duke 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, | |
| 2024 | Alison Gopnik | Effect of Language on Thought, Development of a Theory of Mind,[5] Causal Learning[6] | University of California, Berkeley, |