Switch to: References

Add citations

You must login to add citations.
  1. (1 other version)The best game in town: The reemergence of the language-of-thought hypothesis across the cognitive sciences.Jake Quilty-Dunn, Nicolas Porot & Eric Mandelbaum - 2023 - Behavioral and Brain Sciences 46:e261.
    Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language-of-thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate–argument structure; (iv) logical operators; (v) inferential (...)
    Download  
     
    Export citation  
     
    Bookmark   13 citations  
  • Divergences in color perception between deep neural networks and humans.Ethan O. Nadler, Elise Darragh-Ford, Bhargav Srinivasa Desikan, Christian Conaway, Mark Chu, Tasker Hull & Douglas Guilbeault - 2023 - Cognition 241 (C):105621.
    Download  
     
    Export citation  
     
    Bookmark  
  • Toward biologically plausible artificial vision.Mason Westfall - 2023 - Behavioral and Brain Sciences 46:e290.
    Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision – found in reinforcement-learning agents navigating artificial three-dimensional environments – can be expected to be more human-like. Recent work suggests that language-like representations substantially improves these agents’ performance, lending some indirect support to the language-of-thought hypothesis (LoTH).
    Download  
     
    Export citation  
     
    Bookmark  
  • Spatial relation categorization in infants and deep neural networks.Guy Davidson, A. Emin Orhan & Brenden M. Lake - 2024 - Cognition 245 (C):105690.
    Download  
     
    Export citation  
     
    Bookmark  
  • Toward an Atlas of Canonical Cognitive Mechanisms.Angelo Pirrone & Konstantinos Tsetsos - 2023 - Cognitive Science 47 (2):e13243.
    A central goal in Cognitive Science is understanding the mechanisms that underlie cognition. Here, we contend that Cognitive Science, despite intense multidisciplinary efforts, has furnished surprisingly few mechanistic insights. We attribute this slow mechanistic progress to the fact that cognitive scientists insist on performing underdetermined exercises, deriving overparametrized mechanistic theories of complex behaviors and seeking validation of these theories to the elusive notions of optimality and biological plausibility. We propose that mechanistic progress in Cognitive Science will accelerate once cognitive scientists (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Solving Bongard Problems With a Visual Language and Pragmatic Constraints.Stefan Depeweg, Contantin A. Rothkopf & Frank Jäkel - 2024 - Cognitive Science 48 (5):e13432.
    More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial subset of them. In the system presented here, visual features are extracted through image processing and then translated into a symbolic visual vocabulary. We introduce a formal language (...)
    Download  
     
    Export citation  
     
    Bookmark