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  1. The Oxford Handbook of Causal Reasoning.Michael Waldmann (ed.) - 2017 - Oxford, England: Oxford University Press.
    Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...)
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  • A History of AI and Law in 50 Papers: 25 Years of the International Conference on AI and Law. [REVIEW]Trevor Bench-Capon, Michał Araszkiewicz, Kevin Ashley, Katie Atkinson, Floris Bex, Filipe Borges, Daniele Bourcier, Paul Bourgine, Jack G. Conrad, Enrico Francesconi, Thomas F. Gordon, Guido Governatori, Jochen L. Leidner, David D. Lewis, Ronald P. Loui, L. Thorne McCarty, Henry Prakken, Frank Schilder, Erich Schweighofer, Paul Thompson, Alex Tyrrell, Bart Verheij, Douglas N. Walton & Adam Z. Wyner - 2012 - Artificial Intelligence and Law 20 (3):215-319.
    We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of the development of AI and Law, while often offering some personal reactions and reflections. As a whole, the subsections build into (...)
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  • Concepts and Conceptual Change.Paul R. Thagard - 1990 - Synthese 82 (2):255-74.
    This paper argues that questions concerning the nature of concepts that are central in cognitive psychology are also important to epistemology and that there is more to conceptual change than mere belief revision. Understanding of epistemic change requires appreciation of the complex ways in which concepts are structured and organized and of how this organization can affect belief revision. Following a brief summary of the psychological functions of concepts and a discussion of some recent accounts of what concepts are, I (...)
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  • High-Level Perception, Representation, and Analogy:A Critique of Artificial Intelligence Methodology.David J. Chalmers, Robert M. French & Douglas R. Hofstadter - 1992 - Journal of Experimental and Theoretical Artificial Intellige 4 (3):185 - 211.
    High-level perception--”the process of making sense of complex data at an abstract, conceptual level--”is fundamental to human cognition. Through high-level perception, chaotic environmen- tal stimuli are organized into the mental representations that are used throughout cognitive pro- cessing. Much work in traditional artificial intelligence has ignored the process of high-level perception, by starting with hand-coded representations. In this paper, we argue that this dis- missal of perceptual processes leads to distorted models of human cognition. We examine some existing artificial-intelligence models--”notably (...)
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  • Analogical Episodes Are More Likely to Be Blended Than Superficially Similar Ones.Veselina Feldman & Boicho Kokinov - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
     
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  • Varieties of Noise: Analogical Reasoning in Synthetic Biology.Tarja Knuuttila & Andrea Loettgers - 2014 - Studies in History and Philosophy of Science Part A 48:76-88.
    The picture of synthetic biology as a kind of engineering science has largely created the public understanding of this novel field, covering both its promises and risks. In this paper, we will argue that the actual situation is more nuanced and complex. Synthetic biology is a highly interdisciplinary field of research located at the interface of physics, chemistry, biology, and computational science. All of these fields provide concepts, metaphors, mathematical tools, and models, which are typically utilized by synthetic biologists by (...)
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  • Two Ways of Analogy: Extending the Study of Analogies to Mathematical Domains.Dirk Schlimm - 2008 - Philosophy of Science 75 (2):178-200.
    The structure-mapping theory has become the de-facto standard account of analogies in cognitive science and philosophy of science. In this paper I propose a distinction between two kinds of domains and I show how the account of analogies based on structure-preserving mappings fails in certain (object-rich) domains, which are very common in mathematics, and how the axiomatic approach to analogies, which is based on a common linguistic description of the analogs in terms of laws or axioms, can be used successfully (...)
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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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  • Arguments and Cases: An Inevitable Intertwining. [REVIEW]David B. Skalak & Edwina L. Rissland - 1992 - Artificial Intelligence and Law 1 (1):3-44.
    We discuss several aspects of legal arguments, primarily arguments about the meaning of statutes. First, we discuss how the requirements of argument guide the specification and selection of supporting cases and how an existing case base influences argument formation. Second, we present,our evolving taxonomy of patterns of actual legal argument. This taxonomy builds upon our much earlier work on argument moves and also on our more recent analysis of how cases are used to support arguments for the interpretation of legal (...)
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  • Uncovering the Course of Analogical Mapping Using Eye Tracking.Bartłomiej Kroczek, Iwona Ciechanowska & Adam Chuderski - 2022 - Cognition 225:105140.
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  • Comprehension‐Based Skill Acquisition.Stephanie M. Doane, Young Woo Sohn, Danielle S. McNamara & David Adams - 2000 - Cognitive Science 24 (1):1-52.
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  • Seeing the Unseen: Second-Order Correlation Learning in 7- to 11-Month-Olds.Yevdokiya Yermolayeva & David H. Rakison - 2016 - Cognition 152:87-100.
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  • A Limitation of the Reflex-Arc Approach to Consciousness.J. Steven Reznick & Philip David Zelazo - 1991 - Behavioral and Brain Sciences 14 (4):692-692.
  • Computational Exploration of Metaphor Comprehension Processes Using a Semantic Space Model.Akira Utsumi - 2011 - Cognitive Science 35 (2):251-296.
    Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization (...)
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  • Constraints on Analogical Inference.Arthur B. Markman - 1997 - Cognitive Science 21 (4):373-418.
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  • Coherence as Constraint Satisfaction.Paul Thagard & Karsten Verbeurgt - 1998 - Cognitive Science 22 (1):1-24.
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  • Language Helps Children Succeed on a Classic Analogy Task.Stella Christie & Dedre Gentner - 2014 - Cognitive Science 38 (2):383-397.
    Adult humans show exceptional relational ability relative to other species. In this research, we trace the development of this ability in young children. We used a task widely used in comparative research—the relational match-to-sample task, which requires participants to notice and match the identity relation: for example, AA should match BB instead of CD. Despite the simplicity of this relation, children under 4 years of age failed to pass this test (Experiment 1), and their performance did not improve even with (...)
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  • Integrating Analogical Mapping and General Problem Solving: The Path‐Mapping Theory.Dario D. Salvucci & John R. Anderson - 2001 - Cognitive Science 25 (1):67-110.
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  • Semantic Grounding in Models of Analogy: An Environmental Approach.Michael Ramscar & Daniel Yarlett - 2003 - Cognitive Science 27 (1):41-71.
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  • Relations, Objects, and the Composition of Analogies.Dedre Gentner & Kenneth J. Kurtz - 2006 - Cognitive Science 30 (4):609-642.
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  • Solving Geometric Analogy Problems Through Two‐Stage Analogical Mapping.Andrew Lovett, Emmett Tomai, Kenneth Forbus & Jeffrey Usher - 2009 - Cognitive Science 33 (7):1192-1231.
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  • Constraints on Analogical Mapping: A Comparison of Three Models.Mark T. Keane, Tim Ledgeway & Stuart Duff - 1994 - Cognitive Science 18 (3):387-438.
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  • CAB: Connectionist Analogy Builder.Levi B. Larkey & Bradley C. Love - 2003 - Cognitive Science 27 (5):781-794.
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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.
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  • The One‐to‐One Constraint in Analogical Mapping and Inference.Daniel C. Krawczyk, Keith J. Holyoak & John E. Hummel - 2005 - Cognitive Science 29 (5):797-806.
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  • Integrating Structure and Meaning: A Distributed Model of Analogical Mapping.Chris Eliasmith & Paul Thagard - 2001 - Cognitive Science 25 (2):245-286.
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  • Efficient Creativity: Constraint‐Guided Conceptual Combination.Fintan J. Costello & Mark T. Keane - 2000 - Cognitive Science 24 (2):299-349.
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  • A Memory‐Based Theory of Verbal Cognition.Simon Dennis - 2005 - Cognitive Science 29 (2):145-193.
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  • Conceptual Integration Networks.Gilles Fauconnier & Mark Turner - 1998 - Cognitive Science 22 (2):133-187.
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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.
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  • On the Spontaneous Discovery of a Mathematical Relation During Problem Solving.James A. Dixon & Ashley S. Bangert - 2004 - Cognitive Science 28 (3):433-449.
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  • Varieties of Sameness: The Impact of Relational Complexity on Perceptual Comparisons.James K. Kroger, Keith J. Holyoak & John E. Hummel - 2004 - Cognitive Science 28 (3):335-358.
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  • Mapping Relational Structure in Spatial Reasoning.Merideth Gattis - 2004 - Cognitive Science 28 (4):589-610.
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  • Adversarial Problem Solving: Modeling an Opponent Using Explanatory Coherence.Paul Thagard - 1992 - Cognitive Science 16 (1):123-149.
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  • Processes of Similarity Judgment.Levi B. Larkey & Arthur B. Markman - 2005 - Cognitive Science 29 (6):1061-1076.
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  • The Neural Correlates of Analogy Component Processes.John-Dennis Parsons & Jim Davies - 2022 - Cognitive Science 46 (3):e13116.
    Cognitive Science, Volume 46, Issue 3, March 2022.
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  • What Difference Reveals About Similarity.Eyal Sagi, Dedre Gentner & Andrew Lovett - 2012 - Cognitive Science 36 (6):1019-1050.
    Detecting that two images are different is faster for highly dissimilar images than for highly similar images. Paradoxically, we showed that the reverse occurs when people are asked to describe how two images differ—that is, to state a difference between two images. Following structure-mapping theory, we propose that this disassociation arises from the multistage nature of the comparison process. Detecting that two images are different can be done in the initial (local-matching) stage, but only for pairs with low overlap; thus, (...)
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  • Schaffner’s Model of Theory Reduction: Critique and Reconstruction.Rasmus Gr⊘Nfeldt Winther - 2009 - Philosophy of Science 76 (2):119-142.
    Schaffner’s model of theory reduction has played an important role in philosophy of science and philosophy of biology. Here, the model is found to be problematic because of an internal tension. Indeed, standard antireductionist external criticisms concerning reduction functions and laws in biology do not provide a full picture of the limits of Schaffner’s model. However, despite the internal tension, his model usefully highlights the importance of regulative ideals associated with the search for derivational, and embedding, deductive relations among mathematical (...)
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  • Mind, Society, and the Growth of Knowledge.Paul Thagard - 1994 - Philosophy of Science 61 (4):629-645.
    Explanations of the growth of scientific knowledge can be characterized in terms of logical, cognitive, and social schemas. But cognitive and social schemas are complementary rather than competitive, and purely social explanations of scientific change are as inadequate as purely cognitive explanations. For example, cognitive explanations of the chemical revolution must be supplemented by and combined with social explanations, and social explanations of the rise of the mechanical world view must be supplemented by and combined with cognitive explanations. Rational appraisal (...)
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  • The Emergence of Analogy. Analogical Reasoning as a Constraint Satisfaction Process.Jan Van Dormael - 1990 - Philosophica 46 (2):65-76.
     
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  • On Fodor's First Law of the Nonexistence of Cognitive Science.Gregory L. Murphy - 2019 - Cognitive Science 43 (5):e12735.
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  • Understanding Blended Multi-Source Arguments as Arguments From Partial Analogies.Marcello Guarini - 2010 - Ratio Juris 23 (1):65-100.
    This paper identifies a type of multi-source (case-based) reasoning and differentiates it from other types of analogical reasoning. Work in cognitive science on mental space mapping or conceptual blending is used to better understand this type of reasoning. The type of argument featured herein will be shown to be a kind of source-blended argument. While it possesses some similarities to traditionally conceived analogical arguments, there are important differences as well. The triple contract (a key development in the usury debates of (...)
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  • The Role of Surface Similarity in Analogical Retrieval: Bridging the Gap Between the Naturalistic and the Experimental Traditions.Máximo Trench & Ricardo A. Minervino - 2015 - Cognitive Science 39 (6):1292-1319.
    Blanchette and Dunbar have claimed that when participants are allowed to draw on their own source analogs in the service of analogical argumentation, retrieval is less constrained by surface similarity than traditional experiments suggest. In two studies, we adapted this production paradigm to control for the potentially distorting effects of analogy fabrication and uneven availability of close and distant sources in memory. Experiment 1 assessed whether participants were reminded of central episodes from popular movies while generating analogies for superficially similar (...)
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  • Making Probabilistic Relational Categories Learnable.Wookyoung Jung & John E. Hummel - 2015 - Cognitive Science 39 (6):1259-1291.
    Theories of relational concept acquisition based on structured intersection discovery predict that relational concepts with a probabilistic structure ought to be extremely difficult to learn. We report four experiments testing this prediction by investigating conditions hypothesized to facilitate the learning of such categories. Experiment 1 showed that changing the task from a category-learning task to choosing the “winning” object in each stimulus greatly facilitated participants' ability to learn probabilistic relational categories. Experiments 2 and 3 further investigated the mechanisms underlying this (...)
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  • Dissociating Consciousness From Cognition.David Spiegel - 1991 - Behavioral and Brain Sciences 14 (4):695-696.
  • Reasoning With Causal Cycles.Bob Rehder - 2017 - Cognitive Science 41 (S5):944-1002.
    This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new formalisms that allow cycles are introduced and evaluated. Dynamic Bayesian networks represent cycles by unfolding them over time. Chain graphs augment CGMs by allowing the presence of undirected links (...)
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  • Extending SME to Handle Large‐Scale Cognitive Modeling.Kenneth D. Forbus, Ronald W. Ferguson, Andrew Lovett & Dedre Gentner - 2017 - Cognitive Science 41 (5):1152-1201.
    Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological evidence (...)
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  • Case-to-Case Arguments.Katharina Stevens - 2018 - Argumentation 32 (3):431-455.
    Arguers sometimes cite a decision made in an earlier situation as a reason for making the equivalent decision in a later situation. I argue that there are two kinds of “case-to-case arguments”. First, there are arguments by precedent, which cite the mere existence of the past decision as a reason to decide in the same way again now, independent of the past decision’s merits. Second, there are case-to-case arguments from parralel reasoning which presuppose that the past decision was justified and (...)
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  • Prefacr.Lorenzo Magnani, Nancy J. Nersessian & Paul Thagard - 2000 - Foundations of Science 5 (2):121-127.