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  1. Deduction by children and animals: Does it follow the Johnson-Laird & Byrne model?Hank Davis - 1993 - Behavioral and Brain Sciences 16 (2):344-344.
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  • On rules, models and understanding.Jonathan St B. T. Evans - 1993 - Behavioral and Brain Sciences 16 (2):345-346.
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  • Toward a unified behavioral and brain science.Jerome A. Feldman - 1993 - Behavioral and Brain Sciences 16 (3):458-458.
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  • How our brains reason logically.Markus Knauff - 2007 - Topoi 26 (1):19-36.
    The aim of this article is to strengthen links between cognitive brain research and formal logic. The work covers three fundamental sorts of logical inferences: reasoning in the propositional calculus, i.e. inferences with the conditional “if...then”, reasoning in the predicate calculus, i.e. inferences based on quantifiers such as “all”, “some”, “none”, and reasoning with n-place relations. Studies with brain-damaged patients and neuroimaging experiments indicate that such logical inferences are implemented in overlapping but different bilateral cortical networks, including parts of the (...)
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  • Conditional reasoning and causation.Denise D. Cummins, Todd Lubart, Olaf Alksnis & Robert Rist - 1991 - Memory and Cognition 19 (3):274-282.
    An experiment was conducted to investigate the relative contributions of syntactic form and content to conditional reasoning. The content domain chosen was that of causation. Conditional statements that described causal relationships were embedded in simple arguments whose entailments are governed by the rules -of truth-functional logic. The causal statements differed in terms of the number of alternative causes and disabling conditions that characterized the causal relationship. Subjects were required to judge whether or not each argument’s conclusion could be accepted. Judgments (...)
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  • The processing of negations in conditional reasoning: A meta-analytic case study in mental model and/or mental logic theory.Walter J. Schroyens, Walter Schaeken & Géry D'Ydewalle - 2001 - Thinking and Reasoning 7 (2):121-172.
    We present a meta-analytic review on the processing of negations in conditional reasoning about affirmation problems (Modus Ponens: “MP”, Affirmation of the Consequent “AC”) and denial problems (Denial of the Antecedent “DA”, and Modus Tollens “MT”). Findings correct previous generalisations about the phenomena. First, the effects of negation in the part of the conditional about which an inference is made, are not constrained to denial problems. These inferential-negation effects are also observed on AC. Second, there generally are reliable effects of (...)
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  • Nonsentential representation and nonformality.Keith Stenning & Jon Oberlander - 1993 - Behavioral and Brain Sciences 16 (2):365-366.
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  • Self-organizing neural models of categorization, inference and synchrony.Stephen Grossberg - 1993 - Behavioral and Brain Sciences 16 (3):460-461.
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  • Probabilistic effects in data selection.Mike Oaksford, Nick Chater & Becki Grainger - 1999 - Thinking and Reasoning 5 (3):193 – 243.
    Four experiments investigated the effects of probability manipulations on the indicative four card selection task (Wason, 1966, 1968). All looked at the effects of high and low probability antecedents (p) and consequents (q) on participants' data selections when determining the truth or falsity of a conditional rule, if p then q . Experiments 1 and 2 also manipulated believability. In Experiment 1, 128 participants performed the task using rules with varied contents pretested for probability of occurrence. Probabilistic effects were observed (...)
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  • Strategies during complex conditional inferences.Kristien Dieussaert, Walter Schaeken, Walter Schroyens & Gery D'Ydewalle - 2000 - Thinking and Reasoning 6 (2):125 – 160.
    In certain contexts reasoners reject instances of the valid Modus Ponens and Modus Tollens inference form in conditional arguments. Byrne (1989) observed this suppression effect when a conditional premise is accompanied by a conditional containing an additional requirement. In an earlier study, Rumain, Connell, and Braine (1983) observed suppression of the invalid inferences "the denial of the antecedent" and "the affirmation of the consequent" when a conditional premise is accompanied by a conditional containing an alternative requirement. Here we present three (...)
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  • From the descriptive to the normative in psychology and logic.Paul Thagard - 1982 - Philosophy of Science 49 (1):24-42.
    The aim of this paper is to describe a methodology for revising logical principles in the light of empirical psychological findings. Historical philosophy of science and wide reflective equilibrium in ethics are considered as providing possible models for arguing from the descriptive to the normative. Neither is adequate for the psychology/logic case, and a new model is constructed, employing criteria for evaluating inferential systems. Once we have such criteria, the notion of reflective equilibrium becomes redundant.
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  • : Introduction: Why is understanding the development of reasoning important?Henry Markovits & Pierre Barrouillet - 2004 - Thinking and Reasoning 10 (2):113-121.
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  • Models for deontic deduction.K. I. Manktelow - 1993 - Behavioral and Brain Sciences 16 (2):357-357.
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  • Deductive reasoning: What are taken to be the premises and how are they interpreted?Samuel Fillenbaum - 1993 - Behavioral and Brain Sciences 16 (2):348-349.
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  • On modes of explanation.Rachel Joffe Falmagne - 1993 - Behavioral and Brain Sciences 16 (2):346-347.
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  • Mental models cannot exclude mental logic and make little sense without it.Martin D. S. Braine - 1993 - Behavioral and Brain Sciences 16 (2):338-339.
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  • Should first-order logic be neurally plausible?David S. Touretzky & Scott E. Fahlman - 1993 - Behavioral and Brain Sciences 16 (3):474-475.
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  • Competing, or perhaps complementary, approaches to the dynamic-binding problem, with similar capacity limitations.Graeme S. Halford - 1993 - Behavioral and Brain Sciences 16 (3):461-462.
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  • What we know and the LTKB.Stanley Munsat - 1993 - Behavioral and Brain Sciences 16 (3):466-467.
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  • From symbols to neurons: Are we there yet?Garrison W. Cottrell - 1993 - Behavioral and Brain Sciences 16 (3):454-454.
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  • Connectionism and syntactic binding of concepts.Georg Dorffner - 1993 - Behavioral and Brain Sciences 16 (3):456-457.
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  • Temporal and spatial relations in sentential reasoning.Csongor Juhos, Ana Cristina Quelhas & Philip N. Johnson-Laird - 2012 - Cognition 122 (3):393-404.
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  • Normative theory and the human mind.Rachel Joffe Falmagne - 1985 - Behavioral and Brain Sciences 8 (4):750-751.
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  • Rats and infants as propositional reasoners: A plausible possibility?Leyre Castro & Edward A. Wasserman - 2009 - Behavioral and Brain Sciences 32 (2):203-204.
    Mitchell et al. contemplate the possibility of rats being capable of propositional reasoning. We suggest that this is an unlikely and unsubstantiated possibility. Nonhuman animals and human infants do learn about the contingencies in the world; however, such learning seems not to be based on propositional reasoning, but on more elementary associative processes.
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  • Rules and illusions: A critical study of Rips's the psychology of proof. [REVIEW]Philip N. Johnson-Laird - 1997 - Minds and Machines 7 (3):387-407.
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  • Synchronization and cognitive carpentry: From systematic structuring to simple reasoning. E. Koerner - 1993 - Behavioral and Brain Sciences 16 (3):465-466.
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  • Conditionals and inferential connections: toward a new semantics.Igor Douven, Shira Elqayam, Henrik Singmann & Janneke van Wijnbergen-Huitink - 2020 - Thinking and Reasoning 26 (3):311-351.
    In previous published research (“Conditionals and Inferential Connections: A Hypothetical Inferential Theory,” Cognitive Psychology, 2018), we investigated experimentally what role the presence and strength of an inferential connection between a conditional’s antecedent and consequent plays in how people process that conditional. Our analysis showed the strength of that connection to be strongly predictive of whether participants evaluated the conditional as true, false, or neither true nor false. In this article, we re-analyse the data from our previous research, now focussing on (...)
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  • Human rationality: Essential conflicts, multiple ideals.Jonathan E. Adler - 1983 - Behavioral and Brain Sciences 6 (2):245-246.
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  • Decisions with indeterminate probabilities.Teddy Seidenfeld - 1983 - Behavioral and Brain Sciences 6 (2):259-261.
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  • Mental models, more or less.Thad A. Polk - 1993 - Behavioral and Brain Sciences 16 (2):362-363.
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  • Popper's severity of test as an intuitive probabilistic model of hypothesis testing.Fenna H. Poletiek - 2009 - Behavioral and Brain Sciences 32 (1):99-100.
    Severity of Test (SoT) is an alternative to Popper's logical falsification that solves a number of problems of the logical view. It was presented by Popper himself in 1963. SoT is a less sophisticated probabilistic model of hypothesis testing than Oaksford & Chater's (O&C's) information gain model, but it has a number of striking similarities. Moreover, it captures the intuition of everyday hypothesis testing.
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  • Theories of reasoning and the computational explanation of everyday inference.Mike Oaksford & Nick Chater - 1995 - Thinking and Reasoning 1 (2):121 – 152.
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  • Can conditionals explain explanations? A modus ponens model of B because A.Simone Sebben & Johannes Ullrich - 2021 - Cognition 215 (C):104812.
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  • Ethereal oscillations.Malcolm P. Young - 1993 - Behavioral and Brain Sciences 16 (3):476-477.
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  • Psychology and the foundations of rational belief.Ryan D. Tweney, Michael E. Doherty & Clifford R. Mynatt - 1983 - Behavioral and Brain Sciences 6 (2):262-263.
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  • Scientific thinking and mental models.Ryan D. Tweney - 1993 - Behavioral and Brain Sciences 16 (2):366-367.
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  • Inductive reasoning: Competence or skill?Christopher Jepson, David H. Krantz & Richard E. Nisbett - 1983 - Behavioral and Brain Sciences 6 (3):494.
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  • Everyday reasoning and logical inference.Jon Barwise - 1993 - Behavioral and Brain Sciences 16 (2):337-338.
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  • Making a middling mousetrap.Michael R. W. Dawson & Istvan Berkeley - 1993 - Behavioral and Brain Sciences 16 (3):454-455.
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  • Models, rules and expertise.Rosemary J. Stevenson - 1993 - Behavioral and Brain Sciences 16 (2):366-366.
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  • A theory of probability should tutor our intuitions.Glenn Shafer - 1983 - Behavioral and Brain Sciences 6 (3):508.
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  • A step toward modeling reflexive reasoning.Lokendra Shastri & Venkat Ajjanagadde - 1993 - Behavioral and Brain Sciences 16 (3):477-494.
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  • The psychology of knights and knaves.Lance J. Rips - 1989 - Cognition 31 (2):85-116.
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  • The logic is in the representation.Russell Revlin - 1983 - Behavioral and Brain Sciences 6 (2):259-259.
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  • 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.
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  • Confirming confirmation bias.P. Pollard - 1983 - Behavioral and Brain Sciences 6 (2):258-259.
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  • Making reasoning more reasonable: Event-coherence and assemblies.Günther Palm - 1993 - Behavioral and Brain Sciences 16 (3):470-470.
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  • Psychological implications of the synchronicity hypothesis.Stellan Ohlsson - 1993 - Behavioral and Brain Sciences 16 (3):469-469.
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  • The uncertain reasoner: Bayes, logic, and rationality.Mike Oaksford & Nick Chater - 2009 - Behavioral and Brain Sciences 32 (1):105-120.
    Human cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. In Bayesian Rationality we argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there is (...)
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  • Psychology, statistics, and analytical epistemology.Richard E. Nisbett & Paul Thagard - 1983 - Behavioral and Brain Sciences 6 (2):257-258.
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