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  1. Visual models in analogical problem solving.Jim Davies, Nancy J. Nersessian & Ashok K. Goel - 2005 - Foundations of Science 10 (1):133-152.
    Visual analogy is believed to be important in human problem solving. Yet, there are few computational models of visual analogy. In this paper, we present a preliminary computational model of visual analogy in problem solving. The model is instantiated in a computer program, called Galatea, which uses a language for representing and transferring visual information called Privlan. We describe how the computational model can account for a small slice of a cognitive-historical analysis of Maxwell’s reasoning about electromagnetism.
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  • Episodic Indexing: A Model of Memory for Attention Events.Erik M. Altmann & Bonnie E. John - 1999 - Cognitive Science 23 (2):117-156.
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  • Knowledge of counterfactual interventions through cognitive models of mechanisms.Jonathan Waskan - 2008 - International Studies in the Philosophy of Science 22 (3):259 – 275.
    Here I consider the relative merits of two recent models of explanation, James Woodward's interventionist-counterfactual model and the model model. According to the former, explanations are largely constituted by information about the consequences of counterfactual interventions. Problems arise for this approach because countless relevant interventions are possible in most cases and because it overlooks other kinds of equally relevant information. According the model model, explanations are largely constituted by cognitive models of actual mechanisms. On this approach, explanations tend not to (...)
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  • Intrinsic cognitive models.Jonathan A. Waskan - 2003 - Cognitive Science 27 (2):259-283.
    Theories concerning the structure, or format, of mental representation should (1) be formulated in mechanistic, rather than metaphorical terms; (2) do justice to several philosophical intuitions about mental representation; and (3) explain the human capacity to predict the consequences of worldly alterations (i.e., to think before we act). The hypothesis that thinking involves the application of syntax-sensitive inference rules to syntactically structured mental representations has been said to satisfy all three conditions. An alternative hypothesis is that thinking requires the construction (...)
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  • Are theories of imagery theories of imagination? An active perception approach to conscious mental content.Nigel J. T. Thomas - 1999 - Cognitive Science 23 (2):207-245.
    Can theories of mental imagery, conscious mental contents, developed within cognitive science throw light on the obscure (but culturally very significant) concept of imagination? Three extant views of mental imagery are considered: quasi‐pictorial, description, and perceptual activity theories. The first two face serious theoretical and empirical difficulties. The third is (for historically contingent reasons) little known, theoretically underdeveloped, and empirically untried, but has real explanatory potential. It rejects the “traditional” symbolic computational view of mental contents, but is compatible with recentsituated (...)
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  • Societies of minds: Science as distributed computing.Paul Thagard - 1991 - Studies in History and Philosophy of Science Part A 24 (1):49-67.
    Science is studied in very different ways by historians, philosophers, psychologists, and sociologists. Not only do researchers from different fields apply markedly different methods, they also tend to focus on apparently disparate aspects of science. At the farthest extremes, we find on one side some philosophers attempting logical analyses of scientific knowledge, and on the other some sociologists maintaining that all knowledge is socially constructed. This paper is an attempt to view history, philosophy, psychology, and sociology of science from a (...)
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  • Supermachines and superminds.Eric Steinhart - 2003 - Minds and Machines 13 (1):155-186.
    If the computational theory of mind is right, then minds are realized by machines. There is an ordered complexity hierarchy of machines. Some finite machines realize finitely complex minds; some Turing machines realize potentially infinitely complex minds. There are many logically possible machines whose powers exceed the Church–Turing limit (e.g. accelerating Turing machines). Some of these supermachines realize superminds. Superminds perform cognitive supertasks. Their thoughts are formed in infinitary languages. They perceive and manipulate the infinite detail of fractal objects. They (...)
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  • Modeling Mental Spatial Reasoning About Cardinal Directions.Holger Schultheis, Sven Bertel & Thomas Barkowsky - 2014 - Cognitive Science 38 (8):1521-1561.
    This article presents research into human mental spatial reasoning with orientation knowledge. In particular, we look at reasoning problems about cardinal directions that possess multiple valid solutions , at human preferences for some of these solutions, and at representational and procedural factors that lead to such preferences. The article presents, first, a discussion of existing, related conceptual and computational approaches; second, results of empirical research into the solution preferences that human reasoners actually have; and, third, a novel computational model that (...)
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  • Casimir: An Architecture for Mental Spatial Knowledge Processing.Holger Schultheis & Thomas Barkowsky - 2011 - Topics in Cognitive Science 3 (4):778-795.
    Mental spatial knowledge processing often uses spatio-analogical or quasipictorial representation structures such as spatial mental models or mental images. The cognitive architecture Casimir is designed to provide a framework for computationally modeling human spatial knowledge processing relying on these kinds of representation formats. In this article, we present an overview of Casimir and its components. We briefly describe the long-term memory component and the interaction with external diagrammatic representations. Particular emphasis is placed on Casimir’s working memory and control mechanisms. Regarding (...)
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  • Exploring the Functional Advantages of Spatial and Visual Cognition From an Architectural Perspective.Scott D. Lathrop, Samuel Wintermute & John E. Laird - 2011 - Topics in Cognitive Science 3 (4):796-818.
    We present a general cognitive architecture that tightly integrates symbolic, spatial, and visual representations. A key means to achieving this integration is allowing cognition to move freely between these modes, using mental imagery. The specific components and their integration are motivated by results from psychology, as well as the need for developing a functional and efficient implementation. We discuss functional benefits that result from the combination of multiple content-based representations and the specialized processing units associated with them. Instantiating this theory, (...)
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  • The Manipulation of Images to Handle Indeterminacy in Spatial Reasoning.Thomas R. Ioerger - 1994 - Cognitive Science 18 (4):551-593.
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  • Prolegomena to a cognitive investigation of Euclidean diagrammatic reasoning.Yacin Hamami & John Mumma - 2013 - Journal of Logic, Language and Information 22 (4):421-448.
    Euclidean diagrammatic reasoning refers to the diagrammatic inferential practice that originated in the geometrical proofs of Euclid’s Elements. A seminal philosophical analysis of this practice by Manders (‘The Euclidean diagram’, 2008) has revealed that a systematic method of reasoning underlies the use of diagrams in Euclid’s proofs, leading in turn to a logical analysis aiming to capture this method formally via proof systems. The central premise of this paper is that our understanding of Euclidean diagrammatic reasoning can be fruitfully advanced (...)
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  • Representations and Processes of Human Spatial Competence.Glenn Gunzelmann & Don R. Lyon - 2011 - Topics in Cognitive Science 3 (4):741-759.
    This article presents an approach to understanding human spatial competence that focuses on the representations and processes of spatial cognition and how they are integrated with cognition more generally. The foundational theoretical argument for this research is that spatial information processing is central to cognition more generally, in the sense that it is brought to bear ubiquitously to improve the adaptivity and effectiveness of perception, cognitive processing, and motor action. We describe research spanning multiple levels of complexity to understand both (...)
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  • Resources for Research on Analogy: A Multi-disciplinary Guide.Marcello Guarini, Amy Butchart, Paul Simard Smith & Andrei Moldovan - 2009 - Informal Logic 29 (2):84-197.
    Work on analogy has been done from a number of disciplinary perspectives throughout the history of Western thought. This work is a multidisciplinary guide to theorizing about analogy. It contains 1,406 references, primarily to journal articles and monographs, and primarily to English language material. classical through to contemporary sources are included. The work is classified into eight different sections (with a number of subsections). A brief introduction to each section is provided. Keywords and key expressions of importance to research on (...)
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  • Achievements and fallacies in Hume's account of infinite divisibility.James Franklin - 1994 - Hume Studies 20 (1):85-101.
    Throughout history, almost all mathematicians, physicists and philosophers have been of the opinion that space and time are infinitely divisible. That is, it is usually believed that space and time do not consist of atoms, but that any piece of space and time of non-zero size, however small, can itself be divided into still smaller parts. This assumption is included in geometry, as in Euclid, and also in the Euclidean and non- Euclidean geometries used in modern physics. Of the few (...)
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  • Dynamic Imagery: A Computational Model of Motion and Visual Analogy.David Croft & Paul Thagard - unknown
    This paper describes DIVA (Dynamic Imagery for Visual Analogy), a computational model of visual imagery based on the scene graph, a powerful representational structure widely used in computer graphics. Scene graphs make possible the visual display of complex objects, including the motions of individual objects. Our model combines a semantic-network memory system with computational procedures based on scene graphs. The model can account for people’s ability to produce visual images of moving objects, in particular the ability to use dynamic visual (...)
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  • Philosophy, mathematics and structure.James Franklin - 1995 - Philosopher: revue pour tous 1 (2):31-38.
    An early version of the work on mathematics as the science of structure that appeared later as An Aristotelian Realist Philosophy of Mathematics (2014).
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  • Coherence and analogy articles.Paul Thagard - manuscript
    Barnes, A. and P. Thagard Empathy and analogy. Dialogue: Canadian Philosophical Review, 36: 705-720. HTML Croft, D., & Thagard, P.. Dynamic imagery: A computational model of motion and visual analogy. In L. Magnani and N. Nersessian, Model-based reasoning: Science, technology, values. New York: Kluwer/Plenum, 259-274. PDF only. HTML description of program and code for DIVA.
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  • Extending cognitive architectures with mental imagery.Scott D. Lathrop & John E. Laird - 2009 - In B. Goertzel, P. Hitzler & M. Hutter (eds.), Proceedings of the Second Conference on Artificial General Intelligence. Atlantis Press.
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