16 found
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  1.  56
    The communicative function of ambiguity in language.Steven T. Piantadosi, Harry Tily & Edward Gibson - 2012 - Cognition 122 (3):280-291.
  2.  51
    The logical primitives of thought: Empirical foundations for compositional cognitive models.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2016 - Psychological Review 123 (4):392-424.
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  3.  66
    Bootstrapping in a language of thought: A formal model of numerical concept learning.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2012 - Cognition 123 (2):199-217.
  4.  44
    The Computational Origin of Representation.Steven T. Piantadosi - 2020 - Minds and Machines 31 (1):1-58.
    Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations—whatever they are—must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may give rise (...)
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  5.  63
    Info/information theory: Speakers choose shorter words in predictive contexts.Kyle Mahowald, Evelina Fedorenko, Steven T. Piantadosi & Edward Gibson - 2013 - Cognition 126 (2):313-318.
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  6.  36
    Wordform Similarity Increases With Semantic Similarity: An Analysis of 100 Languages.Isabelle Dautriche, Kyle Mahowald, Edward Gibson & Steven T. Piantadosi - 2017 - Cognitive Science:2149-2169.
    Although the mapping between form and meaning is often regarded as arbitrary, there are in fact well-known constraints on words which are the result of functional pressures associated with language use and its acquisition. In particular, languages have been shown to encode meaning distinctions in their sound properties, which may be important for language learning. Here, we investigate the relationship between semantic distance and phonological distance in the large-scale structure of the lexicon. We show evidence in 100 languages from a (...)
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  7.  20
    Words cluster phonetically beyond phonotactic regularities.Isabelle Dautriche, Kyle Mahowald, Edward Gibson, Anne Christophe & Steven T. Piantadosi - 2017 - Cognition 163 (C):128-145.
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  8.  15
    The cultural origins of symbolic number.David M. O'Shaughnessy, Edward Gibson & Steven T. Piantadosi - 2022 - Psychological Review 129 (6):1442-1456.
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  9.  37
    Word Forms Are Structured for Efficient Use.Kyle Mahowald, Isabelle Dautriche, Edward Gibson & Steven T. Piantadosi - 2018 - Cognitive Science 42 (8):3116-3134.
    Zipf famously stated that, if natural language lexicons are structured for efficient communication, the words that are used the most frequently should require the least effort. This observation explains the famous finding that the most frequent words in a language tend to be short. A related prediction is that, even within words of the same length, the most frequent word forms should be the ones that are easiest to produce and understand. Using orthographics as a proxy for phonetics, we test (...)
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  10.  12
    Learning abstract visual concepts via probabilistic program induction in a Language of Thought.Matthew C. Overlan, Robert A. Jacobs & Steven T. Piantadosi - 2017 - Cognition 168 (C):320-334.
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  11.  8
    Cognitive Mechanisms Underlying Recursive Pattern Processing in Human Adults.Abhishek M. Dedhe, Steven T. Piantadosi & Jessica F. Cantlon - 2023 - Cognitive Science 47 (4):e13273.
    The capacity to generate recursive sequences is a marker of rich, algorithmic cognition, and perhaps unique to humans. Yet, the precise processes driving recursive sequence generation remain mysterious. We investigated three potential cognitive mechanisms underlying recursive pattern processing: hierarchical reasoning, ordinal reasoning, and associative chaining. We developed a Bayesian mixture model to quantify the extent to which these three cognitive mechanisms contribute to adult humans’ performance in a sequence generation task. We further tested whether recursive rule discovery depends upon relational (...)
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  12. Beyond Boolean logic: exploring representation languages for learning complex concepts.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 859--864.
  13.  23
    Origins of Hierarchical Logical Reasoning.Abhishek M. Dedhe, Hayley Clatterbuck, Steven T. Piantadosi & Jessica F. Cantlon - 2023 - Cognitive Science 47 (2):13250.
    Hierarchical cognitive mechanisms underlie sophisticated behaviors, including language, music, mathematics, tool-use, and theory of mind. The origins of hierarchical logical reasoning have long been, and continue to be, an important puzzle for cognitive science. Prior approaches to hierarchical logical reasoning have often failed to distinguish between observable hierarchical behavior and unobservable hierarchical cognitive mechanisms. Furthermore, past research has been largely methodologically restricted to passive recognition tasks as compared to active generation tasks that are stronger tests of hierarchical rules. We argue (...)
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  14.  9
    Stochastic Time‐Series Analyses Highlight the Day‐To‐Day Dynamics of Lexical Frequencies.Cameron Holdaway & Steven T. Piantadosi - 2022 - Cognitive Science 46 (12):e13215.
    Standard models in quantitative linguistics assume that word usage follows a fixed frequency distribution, often Zipf's law or a close relative. This view, however, does not capture the near daily variations in topics of conversation, nor the short-term dynamics of language change. In order to understand the dynamics of human language use, we present a corpus of daily word frequency variation scraped from online news sources every 20 min for more than 2 years. We construct a simple time-varying model with (...)
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  15. The Goldilocks Effect: Infants' preference for stimuli that are neither too predictable nor too surprising.Celeste Kidd, Steven T. Piantadosi & Richard N. Aslin - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2476--2481.
     
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  16.  62
    Quantitative Standards for Absolute Linguistic Universals.Steven T. Piantadosi & Edward Gibson - 2014 - Cognitive Science 38 (4):736-756.
    Absolute linguistic universals are often justified by cross-linguistic analysis: If all observed languages exhibit a property, the property is taken to be a likely universal, perhaps specified in the cognitive or linguistic systems of language learners and users. In many cases, these patterns are then taken to motivate linguistic theory. Here, we show that cross-linguistic analysis will very rarely be able to statistically justify absolute, inviolable patterns in language. We formalize two statistical methods—frequentist and Bayesian—and show that in both it (...)
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