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  1. There is No Need for (Even Fully Fleshed Out) Mental Models to Map Onto Formal Logic.Paul Pollard - 1993 - Behavioral and Brain Sciences 16 (2):363-364.
  • Précis of Deduction.Philip N. Johnson-Laird & Ruth M. J. Byrne - 1993 - Behavioral and Brain Sciences 16 (2):323-333.
    How do people make deductions? The orthodox view in psychology is that they use formal rules of inference like those of a “natural deduction” system.Deductionargues that their logical competence depends, not on formal rules, but on mental models. They construct models of the situation described by the premises, using their linguistic knowledge and their general knowledge. They try to formulate a conclusion based on these models that maintains semantic information, that expresses it parsimoniously, and that makes explicit something not directly (...)
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  • Temporal Synchrony, Dynamic Bindings, and Shruti: A Representational but Nonclassical Model of Reflexive Reasoning.Lokendra Shastri - 1996 - Behavioral and Brain Sciences 19 (2):331-337.
    Lange & Dyer misunderstand what is meant by an “entity” and confuse a medium of representation with the content being represented. This leads them to the erroneous conclusion that SHRUTI will run out of phases and that its representation of bindings lacks semantic content. It is argued that the limit on the number of phases suffices, and SHRUTI can be interpreted as using “dynamic signatures” that offer significant advantages over fixed preexisting signatures. Bonatti refers to three levels of commitment to (...)
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  • Parallel Reasoning in Structured Connectionist Networks: Signatures Versus Temporal Synchrony.Trent E. Lange & Michael G. Dyer - 1996 - Behavioral and Brain Sciences 19 (2):328-331.
    Shastri & Ajjanagadde argue convincingly that both structured connectionist networks and parallel dynamic inferencing are necessary for reflexive reasoning - a kind of inferencing and reasoning that occurs rapidly, spontaneously, and without conscious effort, and which seems necessary for everyday tasks such as natural language understanding. As S&A describe, reflexive reasoning requires a solution to thedynamic binding problem, that is, how to encode systematic and abstract knowledge and instantiate it in specific situations to draw appropriate inferences. Although symbolic artificial intelligence (...)
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  • Shruti's Ontology is Representational.Luca Bonatti - 1996 - Behavioral and Brain Sciences 19 (2):326-328.
    I argue that SHRUTl's ontology is heavily committed to a representational view of mind. This is best seen when one thinks of how SHRUTI could be developed to account for psychological data on deductive reasoning.
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  • Mental Model Theory Versus the Inference Rule Approach in Relational Reasoning.Jean-Baptiste Van der Henst - 2002 - Thinking and Reasoning 8 (3):193 – 203.
    Researchers currently working on relational reasoning typically argue that mental model theory (MMT) is a better account than the inference rule approach (IRA). They predict and observe that determinate (or one-model) problems are easier than indeterminate (or two-model) problems, whereas according to them, IRA should lead to the opposite prediction. However, the predictions attributed to IRA are based on a mistaken argument. The IRA is generally presented in such a way that inference rules only deal with determinate relations and not (...)
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  • Mental Models and the Suppositional Account of Conditionals.Pierre Barrouillet, Caroline Gauffroy & Jean-François Lecas - 2008 - Psychological Review 115 (3):760-771.
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  • Probability in Reasoning: A Developmental Test on Conditionals.Pierre Barrouillet & Caroline Gauffroy - 2015 - Cognition 137:22-39.
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  • Conditionals: A Theory of Meaning, Pragmatics, and Inference.Philip Johnson-Laird & Ruth M. J. Byrne - 2002 - Psychological Review 109 (4):646-678.
    The authors outline a theory of conditionals of the form If A then C and If A then possibly C. The 2 sorts of conditional have separate core meanings that refer to sets of possibilities. Knowledge, pragmatics, and semantics can modulate these meanings. Modulation can add information about temporal and other relations between antecedent and consequent. It can also prevent the construction of possibilities to yield 10 distinct sets of possibilities to which conditionals can refer. The mental representation of a (...)
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  • Strategies in Sentential Reasoning.Jean‐Baptiste Henst, Yingrui Yang & P. N. Johnson‐Laird - 2002 - Cognitive Science 26 (4):425-468.
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  • Model Theory of Deduction: A Unified Computational Approach.Bruno G. Bara, Monica Bucciarelli & Vincenzo Lombardo - 2001 - Cognitive Science 25 (6):839-901.
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  • Strategies in Sentential Reasoning.Jean-Baptiste Van Der Henst, Yingrui Yang & Johnson-Laird N. Philip - 2002 - Cognitive Science 26 (4):425-468.
    Four experiments examined the strategies that individuals develop in sentential reasoning. They led to the discovery of five different strategies. According to the theory proposed in the paper, each of the strategies depends on component tactics, which all normal adults possess, and which are based on mental models. Reasoners vary their use of tactics in ways that are not deterministic. This variation leads different individuals to assemble different strategies, which include the construction of incremental diagram corresponding to mental models, and (...)
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  • A Perceptual Account of Symbolic Reasoning.David Landy, Colin Allen & Carlos Zednik - 2014 - Frontiers in Psychology 5.
    People can be taught to manipulate symbols according to formal mathematical and logical rules. Cognitive scientists have traditionally viewed this capacity—the capacity for symbolic reasoning—as grounded in the ability to internally represent numbers, logical relationships, and mathematical rules in an abstract, amodal fashion. We present an alternative view, portraying symbolic reasoning as a special kind of embodied reasoning in which arithmetic and logical formulae, externally represented as notations, serve as targets for powerful perceptual and sensorimotor systems. Although symbolic reasoning often (...)
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  • Mental Models and Temporal Reasoning.Walter Schaeken, P. N. Johnson-Laird & Gery D'Ydewalle - 1996 - Cognition 60 (3):205-234.
  • The Suppression of Inferences From Counterfactual Conditionals.Orlando Espino & Ruth M. J. Byrne - 2020 - Cognitive Science 44 (4).
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  • An End to the Controversy? A Reply to Rips.Philip N. Johnson-Laird - 1997 - Minds and Machines 7 (3):425-432.
  • Illusory Inferences: A Novel Class of Erroneous Deductions.P. N. Johnson-Laird & Fabien Savary - 1999 - Cognition 71 (3):191-229.
  • The Processes of Inference.Sangeet Khemlani & P. N. Johnson-Laird - 2013 - Argument and Computation 4 (1):4 - 20.
    (2013). The processes of inference. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 4-20. doi: 10.1080/19462166.2012.674060.
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  • Theory, the Final Frontier? A Corpus-Based Analysis of the Role of Theory in Psychological Articles.Sieghard Beller & Andrea Bender - 2017 - Frontiers in Psychology 8.
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  • Processing Capacity Defined by Relational Complexity: Implications for Comparative, Developmental, and Cognitive Psychology.Graeme S. Halford, William H. Wilson & Steven Phillips - 1998 - Behavioral and Brain Sciences 21 (6):803-831.
    Working memory limits are best defined in terms of the complexity of the relations that can be processed in parallel. Complexity is defined as the number of related dimensions or sources of variation. A unary relation has one argument and one source of variation; its argument can be instantiated in only one way at a time. A binary relation has two arguments, two sources of variation, and two instantiations, and so on. Dimensionality is related to the number of chunks, because (...)
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  • Information Processing and Constraint Satisfaction in Wason’s Selection Task.Emmanuel Genot - 2012 - In Jesus M. Larrazabal (ed.), Cognition, reasoning, emotion, Action. CogSc-12. Proceedings of the ILCLI International Workshop on Cognitive Science. pp. 153-162.
    In Wason’s Selection Task, subjects: process information from the instructions and build a mental representation of the problem, then: select a course of action to solve the problem,under the constraints imposed by the instructions. We analyze both aspects as part of a constraint satisfaction problem without assuming Wason’s ‘logical’ solution to be the correct one. We show that outcome of step may induce mutually inconsistent constraints, causing subjects to select at step solutions that violate some of them. Our analysis explains (...)
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  • A Re-Examination of Illusory Inferences Based on Factual Conditional Sentences.Paolo Cherubini, Alberto Mazzocco, Simona Gardini & Aurore Russo - 2001 - Mind and Society 2 (2):9-25.
    According to mental model theory, illusory inferences are a class of deductions in which individuals systematically go wrong. Mental model theory explains them invoking the principle of truth, which is a tendency not to represent models that falsify the premises. In this paper we focus on the illusory problems based on conditional sentences. In three experiments, we show that: (a) rather than not representing models that falsify the conditionals, participants have a different understanding of what falsifies a conditional (Experiment I); (...)
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  • Facts and Possibilities: A Model‐Based Theory of Sentential Reasoning.Sangeet S. Khemlani, Ruth M. J. Byrne & Philip N. Johnson-Laird - 2018 - Cognitive Science 42 (6):1887-1924.
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  • Uncertainty and the Difficulty of Thinking Through Disjunctions.Eldar Shafir - 1994 - Cognition 50 (1-3):403-430.
  • The Analytic Truth and Falsity of Disjunctions.Ana Cristina Quelhas, Célia Rasga & P. N. Johnson‐Laird - 2019 - Cognitive Science 43 (9).
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  • Naive Probability: Model‐Based Estimates of Unique Events.Sangeet S. Khemlani, Max Lotstein & Philip N. Johnson-Laird - 2015 - Cognitive Science 39 (6):1216-1258.
    We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, (...)
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  • The Emergence of Reasoning by the Disjunctive Syllogism in Early Childhood.Shilpa Mody & Susan Carey - 2016 - Cognition 154:40-48.
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  • A Decision Network Account of Reasoning About Other People’s Choices.Alan Jern & Charles Kemp - 2015 - Cognition 142:12-38.
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  • Focussing in Reasoning and Decision Making.P. Legrenzi - 1993 - Cognition 49 (1-2):37-66.
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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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  • Uncorrected Proof.Dan Sperber - unknown
    This work examines how people interpret the sentential connective “or”, which can be viewed either inclusively (A or B or both) or exclusively (A or B but not both). Following up on prior work concerning quantifiers (Noveck, 2001; Noveck & Posada, 2003; Bott & Noveck, 2004) which shows that the common pragmatic interpretation of “some,” some but not all, is conveyed as part of an effortful step, we investigate how extra effort applied to disjunctive statements leads to a pragmatic interpretation (...)
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  • Linguistic-Pragmatic Factors in Interpreting Disjunctions.Ira A. Noveck, Gennaro Chierchia, Florelle Chevaux, Raphaelle Guelminger & Emmanuel Sylvestre - 2002 - Thinking and Reasoning 8 (4):297 – 326.
    The connective or can be treated as an inclusive disjunction or else as an exclusive disjunction. Although researchers are aware of this distinction, few have examined the conditions under which each interpretation should be anticipated. Based on linguistic-pragmatic analyses, we assume that interpretations are initially inclusive before either (a) remaining so, or (b) becoming exclusive by way of an implicature ( but not both ). We point to a class of situations that ought to predispose disjunctions to inclusive interpretations and (...)
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  • Mental Models or Formal Rules?Philip N. Johnson-Laird & Ruth M. J. Byrne - 1993 - Behavioral and Brain Sciences 16 (2):368-380.
  • More Models Just Means More Difficulty.N. E. Wetherick - 1993 - Behavioral and Brain Sciences 16 (2):367-368.
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  • Scientific Thinking and Mental Models.Ryan D. Tweney - 1993 - Behavioral and Brain Sciences 16 (2):366-367.
  • Models, Rules and Expertise.Rosemary J. Stevenson - 1993 - Behavioral and Brain Sciences 16 (2):366-366.
  • Unjustified Presuppositions of Competence.Leah Savion - 1993 - Behavioral and Brain Sciences 16 (2):364-365.
  • Nonsentential Representation and Nonformality.Keith Stenning & Jon Oberlander - 1993 - Behavioral and Brain Sciences 16 (2):365-366.
  • Mental Models, More or Less.Thad A. Polk - 1993 - Behavioral and Brain Sciences 16 (2):362-363.
  • Deduction and Degrees of Belief.David Over - 1993 - Behavioral and Brain Sciences 16 (2):361-362.
  • Do Mental Models Provide an Adequate Account of Syllogistic Reasoning Performance?Stephen E. Newstead - 1993 - Behavioral and Brain Sciences 16 (2):359-360.
  • Mental Models and the Tractability of Everyday Reasoning.Mike Oaksford - 1993 - Behavioral and Brain Sciences 16 (2):360-361.
  • Situation Theory and Mental Models.Alice G. B. ter Meulen - 1993 - Behavioral and Brain Sciences 16 (2):358-359.
  • Visualizing the Possibilities.Bruce J. MacLennan - 1993 - Behavioral and Brain Sciences 16 (2):356-357.
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  • Models for Deontic Deduction.K. I. Manktelow - 1993 - Behavioral and Brain Sciences 16 (2):357-357.
  • Gestalt Theory, Formal Models and Mathematical Modeling.Abraham S. Luchins & Edith H. Luchins - 1993 - Behavioral and Brain Sciences 16 (2):355-356.
  • Architecture and Algorithms: Power Sharing for Mental Models.Robert Inder - 1993 - Behavioral and Brain Sciences 16 (2):354-354.
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  • The Content of Mental Models.Paolo Legrenzi & Maria Sonino - 1993 - Behavioral and Brain Sciences 16 (2):354-355.
  • The Logical Content of Theories of Deduction.Wilfrid Hodges - 1993 - Behavioral and Brain Sciences 16 (2):353-354.
  • Mental Models: Rationality, Representation and Process.D. W. Green - 1993 - Behavioral and Brain Sciences 16 (2):352-353.