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  1. On the spontaneous discovery of a mathematical relation during problem solving.James A. Dixon & Ashley S. Bangert - 2004 - Cognitive Science 28 (3):433-449.
    People spontaneously discover new representations during problem solving. Discovery of a mathematical representation is of special interest, because it shows that the underlying structure of the problem has been extracted. In the current study, participants solved gear‐system problems as part of a game. Although none of the participants initially used a mathematical representation, many discovered a parity‐based, mathematical strategy during problem solving. Two accounts of the spontaneous discovery of mathematical strategies were tested. According to the automatic schema abstraction hypothesis, experience (...)
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  • Psychology in Cognitive Science: 1978–2038.Dedre Gentner - 2010 - Topics in Cognitive Science 2 (3):328-344.
    This paper considers the past and future of Psychology within Cognitive Science. In the history section, I focus on three questions: (a) how has the position of Psychology evolved within Cognitive Science, relative to the other disciplines that make up Cognitive Science; (b) how have particular Cognitive Science areas within Psychology waxed or waned; and (c) what have we gained and lost. After discussing what’s happened since the late 1970s, when the Society and the journal began, I speculate about where (...)
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  • Two types of thought: Evidence from aphasia.Jules Davidoff - 2005 - Behavioral and Brain Sciences 28 (1):20-21.
    Evidence from aphasia is considered that leads to a distinction between abstract and concrete thought processes and hence for a distinction between rules and similarity. It is argued that perceptual classification is inherently a rule-following procedure and these rules are unable to be followed when a patient has difficulty with name comprehension and retrieval.
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  • Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2021 - Synthese 198 (March):2061-2081.
    Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...)
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  • Structure Mapping and Vocabularies for Thinking.Jeffrey Loewenstein - 2017 - Topics in Cognitive Science 9 (3):842-858.
    While extremes tend to capture attention, the ordinary is often most of the story. So it may be with the structure-mapping process. The structure-mapping process can account for such pinnacles of thinking as analogy and metaphor, which can lead to overlooking the mundane, incremental use of structure mapping. Consequently, the current discussion shifts focus to the value of close comparisons between literally similar items for the development of knowledge. The intent is to foster greater integration between process and content as (...)
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  • Perceptual symbol systems.Lawrence W. Barsalou - 1999 - Behavioral and Brain Sciences 22 (4):577-660.
    Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...)
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  • Time-scale dynamics and the development of an embodied cognition.Esther Thelen - 1995 - In Tim van Gelder & Robert Port (eds.), Mind As Motion: Explorations in the Dynamics of Cognition. MIT Press. pp. 69--100.
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  • The Case for Rules in Reasoning.Edward E. Smith, Christopher Langston & Richard E. Nisbett - 1992 - Cognitive Science 16 (1):1-40.
    A number of theoretical positions in psychology—including variants of case‐based reasoning, instance‐based analogy, and connectionist models—maintain that abstract rules are not involved in human reasoning, or at best play a minor role. Other views hold that the use of abstract rules is a core aspect of human reasoning. We propose eight criteria for determining whether or not people use abstract rules in reasoning, and examine evidence relevant to each criterion for several rule systems. We argue that there is substantial evidence (...)
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  • Context and structure: The nature of students' knowledge about three spatial diagram representations.Sean M. Hurley & Laura R. Novick - 2006 - Thinking and Reasoning 12 (3):281 – 308.
    The authors investigated whether college students possess abstract rules concerning the applicability conditions for three spatial diagrams that are important tools for thinking—matrices, networks, and hierarchies. A total of 127 students were asked to select which type of diagram would be best for organising the information in each of several short scenarios. The scenarios were written using three different story contexts: (a) neutral, presenting a real-life situation but not cueing a particular representation; (b) abstract, presenting only variable names and relations; (...)
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  • The rules versus similarity distinction.Emmanuel M. Pothos - 2005 - Behavioral and Brain Sciences 28 (1):1-14.
    The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...)
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  • Intuitive and deliberate judgments are based on common principles.Arie W. Kruglanski & Gerd Gigerenzer - 2011 - Psychological Review 118 (1):97-109.
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  • Analogy and creativity in the works of Johannes Kepler.Dedre Gentner, Sarah Brem, Ron Ferguson, Philip Wolff, Arthur B. Markman & Ken Forbus - 1997 - In T. B. Ward, S. M. Smith & J. Vaid (eds.), Creative Thought: An Investigation of Conceptual Structures and Processes. American Psychological Association.
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  • Reviving Inert Knowledge: Analogical Abstraction Supports Relational Retrieval of Past Events.Dedre Gentner, Jeffrey Loewenstein, Leigh Thompson & Kenneth D. Forbus - 2009 - Cognitive Science 33 (8):1343-1382.
    We present five experiments and simulation studies to establish late analogical abstraction as a new psychological phenomenon: Schema abstraction from analogical examples can revive otherwise inert knowledge. We find that comparing two analogous examples of negotiations at recall time promotes retrieving analogical matches stored in memory—a notoriously elusive effect. Another innovation in this research is that we show parallel effects for real‐life autobiographical memory (Experiments 1–3) and for a controlled memory set (Experiments 4 and 5). Simulation studies show that a (...)
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  • Dissociations in Performance on Novel Versus Irregular Items: Single‐Route Demonstrations With Input Gain in Localist and Distributed Models.Christopher T. Kello, Daragh E. Sibley & David C. Plaut - 2005 - Cognitive Science 29 (4):627-654.
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  • MAC/FAC: A Model of Similarity‐Based Retrieval.Kenneth D. Forbus, Dedre Gentner & Keith Law - 1995 - Cognitive Science 19 (2):141-205.
    We present a model of similarity‐based retrieval that attempts to capture three seemingly contradictory psychological phenomena: (a) structural commonalities are weighed more heavily than surface commonalities in similarity judgments for items in working memory; (b) in retrieval, superficial similarity is more important than structural similarity; and yet (c) purely structural (analogical) remindings e sometimes experienced. Our model, MAC/FAC, explains these phenomena in terms of a two‐stage process. The first stage uses a computationally cheap, non‐structural matcher to filter candidate long‐term memory (...)
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  • The Beginnings of Expertise for Ballads.David C. Rubin, Wanda T. Wallace & Barbara C. Houston - 1993 - Cognitive Science 17 (3):435-462.
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  • Similarity and the development of rules.Dedre Gentner & José Medina - 1998 - Cognition 65 (2-3):263-297.
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  • Understanding expertise and non-analytic cognition in fingerprint discriminations made by humans.Matthew B. Thompson, Jason M. Tangen & Rachel A. Searston - 2014 - Frontiers in Psychology 5.
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