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  1. Judgment under Uncertainty: Heuristics and Biases.Amos Tversky & Daniel Kahneman - 1974 - Science 185 (4157):1124-1131.
    This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...)
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  • The mental representation of parity and number magnitude.Stanislas Dehaene, Serge Bossini & Pascal Giraux - 1993 - Journal of Experimental Psychology: General 122 (3):371.
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  • What some concepts might not be.Sharon Lee Armstrong, Lila R. Gleitman & Henry Gleitman - 1983 - Cognition 13 (1):263--308.
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  • The weirdest people in the world?Joseph Henrich, Steven J. Heine & Ara Norenzayan - 2010 - Behavioral and Brain Sciences 33 (2-3):61-83.
    Behavioral scientists routinely publish broad claims about human psychology and behavior in the world's top journals based on samples drawn entirely from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies. Researchers – often implicitly – assume that either there is little variation across human populations, or that these “standard subjects” are as representative of the species as any other population. Are these assumptions justified? Here, our review of the comparative database from across the behavioral sciences suggests both that there is (...)
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  • Darwin's mistake: Explaining the discontinuity between human and nonhuman minds.Derek C. Penn, Keith J. Holyoak & Daniel J. Povinelli - 2008 - Behavioral and Brain Sciences 31 (2):109-130.
    Over the last quarter century, the dominant tendency in comparative cognitive psychology has been to emphasize the similarities between human and nonhuman minds and to downplay the differences as (Darwin 1871). In the present target article, we argue that Darwin was mistaken: the profound biological continuity between human and nonhuman animals masks an equally profound discontinuity between human and nonhuman minds. To wit, there is a significant discontinuity in the degree to which human and nonhuman animals are able to approximate (...)
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  • Emergence in Cognitive Science.James L. McClelland - 2010 - Topics in Cognitive Science 2 (4):751-770.
    The study of human intelligence was once dominated by symbolic approaches, but over the last 30 years an alternative approach has arisen. Symbols and processes that operate on them are often seen today as approximate characterizations of the emergent consequences of sub- or nonsymbolic processes, and a wide range of constructs in cognitive science can be understood as emergents. These include representational constructs (units, structures, rules), architectural constructs (central executive, declarative memory), and developmental processes and outcomes (stages, sensitive periods, neurocognitive (...)
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  • An interactive activation model of context effects in letter perception: I. An account of basic findings.James L. McClelland & David E. Rumelhart - 1981 - Psychological Review 88 (5):375-407.
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  • Categorization is modulated by transcranial direct current stimulation over left prefrontal cortex.Gary Lupyan, Daniel Mirman, Roy Hamilton & Sharon L. Thompson-Schill - 2012 - Cognition 124 (1):36-49.
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  • A glimpse at the metaphysics of Bongard problems.Alexandre Linhares - 2000 - Artificial Intelligence 121 (1-2):251-270.
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  • Wherein is Human Cognition Systematic?Antoni Gomila, David Travieso & Lorena Lobo - 2012 - Minds and Machines 22 (2):101-115.
    The “systematicity argument” has been used to argue for a classical cognitive architecture (Fodor in The Language of Thought. Harvester Press, London, 1975, Why there still has to be a language of thought? In Psychosemantics, appendix. MIT Press, Cambridge, pp 135–154, 1987; Fodor and Pylyshyn in Cognition 28:3–71, 1988; Aizawa in The systematicity arguments. Kluwer Academic Press, Dordrecht, 2003). From the premises that cognition is systematic and that the best/only explanation of systematicity is compositional structure, it concludes that cognition is (...)
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  • Language, Thought and Compositionality.Jerry A. Fodor - 2002 - Mind and Language 16 (1):1-15.
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  • Language, thought and compositionality.Jerry A. Fodor - 2001 - Mind and Language 16 (1):1-15.
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  • On the Meaning of Words and Dinosaur Bones: Lexical Knowledge Without a Lexicon.Jeffrey L. Elman - 2009 - Cognitive Science 33 (4):547-582.
    Although for many years a sharp distinction has been made in language research between rules and words—with primary interest on rules—this distinction is now blurred in many theories. If anything, the focus of attention has shifted in recent years in favor of words. Results from many different areas of language research suggest that the lexicon is representationally rich, that it is the source of much productive behavior, and that lexically specific information plays a critical and early role in the interpretation (...)
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  • Judgment Under Uncertainty: Heuristics and Biases.Daniel Kahneman, Paul Slovic & Amos Tversky (eds.) - 1982 - Cambridge University Press.
    The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important...
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  • On the internal structure of perceptual and semantic categories.E. H. Rosch - 1973 - In T. E. Moore (ed.), Cognitive Development and the Acquisition of Language. Academic. pp. 111-144.
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  • Magic words: How language augments human computation.Andy Clark - 1998 - In Peter Carruthers & Jill Boucher (eds.), Language and Thought: Interdisciplinary Themes. Cambridge: Cambridge University Press. pp. 162-183.
    Of course, words aren’t magic. Neither are sextants, compasses, maps, slide rules and all the other paraphenelia which have accreted around the basic biological brains of homo sapiens. In the case of these other tools and props, however, it is transparently clear that they function so as to either carry out or to facilitate computational operations important to various human projects. The slide rule transforms complex mathematical problems (ones that would baffle or tax the unaided subject) into simple tasks of (...)
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  • Concepts.Eric Margolis & Stephen Laurence - 2003 - In Stephen P. Stich & Ted A. Warfield (eds.), Blackwell Guide to Philosophy of Mind. Blackwell. pp. 190-213.
    This article provides a critical overview of competing theories of conceptual structure (definitional structure, probabilistic structure, theory structure), including the view that concepts have no structure (atomism). We argue that the explanatory demands that these different theories answer to are best accommodated by an organization in which concepts are taken to have atomic cores that are linked to differing types of conceptual structure.
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  • The instability of graded structure: Implications for the nature of concepts.Lawrence Barsalou - 1987 - In U. Neisser (ed.), Concepts and Conceptual Development: Ecological and Intellectual Factors in Categorization. Cambridge University Press. pp. 101-140.
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