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  1. The “is-ought fallacy” fallacy.Mike Oaksford & Nick Chater - 2011 - Behavioral and Brain Sciences 34 (5):262-263.
    Mere facts about how the world is cannot determine how we ought to think or behave. Elqayam & Evans (E&E) argue that this undercuts the use of rational analysis in explaining how people reason, by ourselves and with others. But this presumed application of the fallacy is itself fallacious. Rational analysis seeks to explain how people do reason, for example in laboratory experiments, not how they ought to reason. Thus, no ought is derived from an is; and rational analysis is (...)
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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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  • Probabilities, causation, and logic programming in conditional reasoning: reply to Stenning and Van Lambalgen.Mike Oaksford & Nick Chater - 2016 - Thinking and Reasoning 22 (3):336-354.
    ABSTRACTOaksford and Chater critiqued the logic programming approach to nonmonotonicity and proposed that a Bayesian probabilistic approach to conditional reasoning provided a more empirically adequate theory. The current paper is a reply to Stenning and van Lambalgen's rejoinder to this earlier paper entitled ‘Logic programming, probability, and two-system accounts of reasoning: a rejoinder to Oaksford and Chater’ in Thinking and Reasoning. It is argued that causation is basic in human cognition and that explaining how abnormality lists are created in LP (...)
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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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  • Précis of bayesian rationality: The probabilistic approach to human reasoning.Mike Oaksford & Nick Chater - 2009 - Behavioral and Brain Sciences 32 (1):69-84.
    According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic – the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining (...)
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  • Mental models, computational explanation and Bayesian cognitive science: Commentary on Knauff and Gazzo Castañeda (2023).Mike Oaksford - 2023 - Thinking and Reasoning 29 (3):371-382.
    Knauff and Gazzo Castañeda (2022) object to using the term “new paradigm” to describe recent developments in the psychology of reasoning. This paper concedes that the Kuhnian term “paradigm” may be queried. What cannot is that the work subsumed under this heading is part of a new, progressive movement that spans the brain and cognitive sciences: Bayesian cognitive science. Sampling algorithms and Bayes nets used to explain biases in JDM can implement the Bayesian new paradigm approach belying any advantages of (...)
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  • Imaging deductive reasoning and the new paradigm.Mike Oaksford - 2015 - Frontiers in Human Neuroscience 9.
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  • Dynamic inference and everyday conditional reasoning in the new paradigm.Mike Oaksford & Nick Chater - 2013 - Thinking and Reasoning 19 (3-4):346-379.
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  • Dual processes, probabilities, and cognitive architecture.Mike Oaksford & Nick Chater - 2012 - Mind and Society 11 (1):15-26.
    It has been argued that dual process theories are not consistent with Oaksford and Chater’s probabilistic approach to human reasoning (Oaksford and Chater in Psychol Rev 101:608–631, 1994 , 2007 ; Oaksford et al. 2000 ), which has been characterised as a “single-level probabilistic treatment[s]” (Evans 2007 ). In this paper, it is argued that this characterisation conflates levels of computational explanation. The probabilistic approach is a computational level theory which is consistent with theories of general cognitive architecture that invoke (...)
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  • Discussion task demands and revising probabilities in the selection task: A comment on green, over, and Pyne.Mike Oaksford - 1998 - Thinking and Reasoning 4 (2):179 – 186.
    Green, Over, and Pyne's (1997) paper (hereafter referred to as ''GOP") seems to provide a novel approach to examining probabilistic effects in Wason's selection task. However, in this comment, it is argued that their chosen experimental paradigm confounds most of their results. The task demands of the externalisation procedure (Green, 1995) enforce a correlation between card selections and the probability of finding a counterexample, which was the main finding of GOP's experiments. Consequently GOP cannot argue that their data support Kirby's (...)
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  • Could Bayesian cognitive science undermine dual-process theories of reasoning?Mike Oaksford - 2023 - Behavioral and Brain Sciences 46:e134.
    Computational-level models proposed in recent Bayesian cognitive science predict both the “biased” and correct responses on many tasks. So, rather than possessing two reasoning systems, people can generate both possible responses within a single system. Consequently, although an account of why people make one response rather than another is required, dual processes of reasoning may not be.
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  • Contrast classes and matching bias as explanations of the effects of negation on conditional reasoning.Mike Oaksford - 2002 - Thinking and Reasoning 8 (2):135 – 151.
    In this paper the arguments for optimal data selection and the contrast class account of negations in the selection task and the conditional inference task are summarised, and contrasted with the matching bias approach. It is argued that the probabilistic contrast class account provides a unified, rational explanation for effects across these tasks. Moreover, there are results that are only explained by the contrast class account that are also discussed. The only major anomaly is the explicit negations effect in the (...)
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  • Conditional probability and the cognitive science of conditional reasoning.Mike Oaksford & Nick Chater - 2003 - Mind and Language 18 (4):359–379.
    This paper addresses the apparent mismatch between the normative and descriptive literatures in the cognitive science of conditional reasoning. Descriptive psychological theories still regard material implication as the normative theory of the conditional. However, over the last 20 years in the philosophy of language and logic the idea that material implication can account for everyday indicative conditionals has been subject to severe criticism. The majority view is now apparently in favour of a subjective conditional probability interpretation. A comparative model fitting (...)
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  • The Bayesian reader: Explaining word recognition as an optimal Bayesian decision process.Dennis Norris - 2006 - Psychological Review 113 (2):327-357.
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  • Set size, assertion form, thematic content and sampling in the selection task.Raymond S. Nickerson, Susan F. Butler & Daniel H. Barch - 2017 - Thinking and Reasoning 23 (2):134-157.
    Participants attempted to solve a modified version of Wason's selection task. Variables were: sizes of the sets referenced by a specified assertion, form of the assertion, thematic content of the assertion, and the need for sampling or not. In Experiment 1, participants were given enough information to determine the truth or falsity of the specified assertion with certainty; in Experiment 2, they had to rely on sampling and could not determine the assertion's truth or falsity with certainty. Performance was better (...)
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  • Hempel's paradox and Wason's selection task: Logical and psychological puzzles of confirmation.Raymond S. Nickerson - 1996 - Thinking and Reasoning 2 (1):1 – 31.
    Hempel's paradox of the ravens has to do with the question of what constitutes confirmation from a logical point of view; Wason 's selection task has been used extensively to investigate how people go about attempting to confirm or disconfirm conditional claims. This paper presents an argument that the paradox is resolved, and that people's typical performance in the selection task can be explained, by consideration of what constitutes an effective strategy for seeking evidence of the tenability of universal or (...)
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  • Deontic Reasoning, Modules and Innateness: A Second Look.Nick Chater & Mike Oaksford - 1996 - Mind and Language 11 (2):191-202.
    Cummins (this issue) puts the case for an innate module for deontic reasoning. We argue that this case is not persuasive. First, we claim that Cummins’evolutionary arguments are neutral regarding whether deontic reasoning is learned or innate. Second, we argue that task differences between deontic and indicative reasoning explain many of the phenomena that Cummins takes as evidence for a deontic module. Third, we argue against the suggestion that deontic reasoning is superior to indicative reasoning, either in adults or children. (...)
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  • Conditional reasoning with realistic material.Stephen E. Newstead - 1997 - Thinking and Reasoning 3 (1):49 – 76.
    Four experiments are reported which investigated the types of truth tables that people associate with conditional sentences and the kinds of inferences that they will draw from them. The present studies differed from most previous ones in using different types of content in the conditionals, for example promises and warnings. It was found that the type of content had a strong and consistent effect on both truth tables and inferences. It is suggested that this is because in real life conditionals (...)
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  • Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain.Jonathan D. Nelson - 2005 - Psychological Review 112 (4):979-999.
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  • Children’s sequential information search is sensitive to environmental probabilities.Jonathan D. Nelson, Bojana Divjak, Gudny Gudmundsdottir, Laura F. Martignon & Björn Meder - 2014 - Cognition 130 (1):74-80.
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  • False memories of the future: A critique of the applications of probabilistic reasoning to the study of cognitive processes.Mihnea Moldoveanu & Ellen Langer - 2002 - Psychological Review 109 (2):358-375.
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  • A rational reinterpretation of dual-process theories.Smitha Milli, Falk Lieder & Thomas L. Griffiths - 2021 - Cognition 217 (C):104881.
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  • Stepwise versus globally optimal search in children and adults.Björn Meder, Jonathan D. Nelson, Matt Jones & Azzurra Ruggeri - 2019 - Cognition 191 (C):103965.
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  • Self‐Directed Learning Favors Local, Rather Than Global, Uncertainty.Douglas B. Markant, Burr Settles & Todd M. Gureckis - 2016 - Cognitive Science 40 (1):100-120.
    Collecting information that one expects to be useful is a powerful way to facilitate learning. However, relatively little is known about how people decide which information is worth sampling over the course of learning. We describe several alternative models of how people might decide to collect a piece of information inspired by “active learning” research in machine learning. We additionally provide a theoretical analysis demonstrating the situations under which these models are empirically distinguishable, and we report a novel empirical study (...)
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  • Troubles with Bayesianism: An introduction to the psychological immune system.Eric Mandelbaum - 2018 - Mind and Language 34 (2):141-157.
    A Bayesian mind is, at its core, a rational mind. Bayesianism is thus well-suited to predict and explain mental processes that best exemplify our ability to be rational. However, evidence from belief acquisition and change appears to show that we do not acquire and update information in a Bayesian way. Instead, the principles of belief acquisition and updating seem grounded in maintaining a psychological immune system rather than in approximating a Bayesian processor.
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  • Superordinate principles in reasoning with causal and deontic conditionals.K. I. Manktelow & N. Fairley - 2000 - Thinking and Reasoning 6 (1):41 – 65.
    We propose that the pragmatic factors that mediate everyday deduction, such as alternative and disabling conditions (e.g. Cummins et al., 1991) and additional requirements (Byrne, 1989) exert their effects on specific inferences because of their perceived relevance to more general principles, which we term SuperPs. Support for this proposal was found first in two causal inference experiments, in which it was shown that specific inferences were mediated by factors that are relevant to a more general principle, while the same inferences (...)
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  • Probabilistic factors in deontic reasoning.K. I. Manktelow, E. J. Sutherland & D. E. Over - 1995 - Thinking and Reasoning 1 (3):201 – 219.
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  • Think-aloud protocols and the selection task: Evidence for relevance effects and rationalisation processes.Erica Lucas & Linden Ball - 2005 - Thinking and Reasoning 11 (1):35 – 66.
    Two experiments are reported that employed think-aloud methods to test predictions concerning relevance effects and rationalisation processes derivable from Evans' (1996) heuristic-analytic theory of the selection task. Evans' account proposes that card selections are triggered by relevance-determining heuristics, with analytic processing serving merely to rationalise heuristically cued decisions. As such, selected cards should be associated with more references to both their facing and their hidden sides than rejected cards, which are not subjected to analytic rationalisation. Experiment 1 used a standard (...)
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  • Focusing in Wason's selection task: Content and instruction effects.Roberta E. Love & Claudius M. Kessler - 1995 - Thinking and Reasoning 1 (2):153 – 182.
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  • Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization.Richard L. Lewis, Andrew Howes & Satinder Singh - 2014 - Topics in Cognitive Science 6 (2):279-311.
    We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of (...)
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  • What does the CRT measure? Poor performance may arise from rational processes.Neil Levy - 2023 - Philosophical Psychology 36 (1):58-84.
    The Cognitive Reflection Test is a widely used measure of the degree to which individuals override an intuitive response and engage in reflection. For both theoretical and practical reasons, it is widely taken to assess an important component of rational thought. In this paper, I will argue that while doing well on the CRT requires valuable cognitive capacities and dispositions, doing badly does not always indicate a lack of such capacities and dispositions. The CRT, I argue, offers respondents implicit (but (...)
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  • Vittorio Girotto.Paolo Legrenzi & Phil Johnson-Laird - 2017 - Thinking and Reasoning 23 (1):1-9.
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  • The Emergence of Organizing Structure in Conceptual Representation.Brenden M. Lake, Neil D. Lawrence & Joshua B. Tenenbaum - 2018 - Cognitive Science 42 (S3):809-832.
    Both scientists and children make important structural discoveries, yet their computational underpinnings are not well understood. Structure discovery has previously been formalized as probabilistic inference about the right structural form—where form could be a tree, ring, chain, grid, etc.. Although this approach can learn intuitive organizations, including a tree for animals and a ring for the color circle, it assumes a strong inductive bias that considers only these particular forms, and each form is explicitly provided as initial knowledge. Here we (...)
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  • Individual differences in conditional reasoning: A dual-process account.Paul A. Klaczynski & David B. Daniel - 2005 - Thinking and Reasoning 11 (4):305 – 325.
    Dual-process theories of conditional reasoning predict that relationships among four basic logical forms, and to intellectual ability and thinking predictions, are most evident when conflict arises between experiential and analytic processing (e.g., Stanovich & West, 2000). To test these predictions, 210 undergraduates were presented with conditionals for which the consequents were either weakly or strongly associated with alternative antecedents (i.e., WA and SA problems, respectively). Consistent with predictions, modus ponens inferences were not related to inferences on the uncertain forms (affirmation (...)
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  • Parameter Inference for Computational Cognitive Models with Approximate Bayesian Computation.Antti Kangasrääsiö, Jussi P. P. Jokinen, Antti Oulasvirta, Andrew Howes & Samuel Kaski - 2019 - Cognitive Science 43 (6):e12738.
    This paper addresses a common challenge with computational cognitive models: identifying parameter values that are both theoretically plausible and generate predictions that match well with empirical data. While computational models can offer deep explanations of cognition, they are computationally complex and often out of reach of traditional parameter fitting methods. Weak methodology may lead to premature rejection of valid models or to acceptance of models that might otherwise be falsified. Mathematically robust fitting methods are, therefore, essential to the progress of (...)
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  • Desirable difficulties during the development of active inquiry skills.George Kachergis, Marjorie Rhodes & Todd Gureckis - 2017 - Cognition 166:407-417.
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  • Positive confirmation bias in the acquisition of information.Martin Jones & Robert Sugden - 2001 - Theory and Decision 50 (1):59-99.
    An experiment is reported which tests for positive confirmation bias in a setting in which individuals choose what information to buy, prior to making a decision. The design – an adaptation of Wason's selection task – reveals the use that subjects make of information after buying it. Strong evidence of positive confirmation bias, in both information acquisition and information use, is found; and this bias is found to be robust to experience. It is suggested that the bias results from a (...)
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  • What happened to the “new paradigm”? Commentary on Knauff and Gazzo Castañeda (2023).P. N. Johnson-Laird & Sangeet Khemlani - 2023 - Thinking and Reasoning 29 (3):409-415.
    Knauff and Gazzo Castañeda (this issue) critique the "new paradigm" – a framework that replaces logic with probabilities – on the grounds that there existed no "old” paradigm for it to supplant. Their position is supported by the large numbers of theories that theorists developed to explain the Wason selection task, syllogisms, and other tasks. We propose some measures to inhibit such facile theorizing, which threatens the viability of cognitive science. We show that robust results exist contrary to the new (...)
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  • Peirce, logic diagrams, and the elementary operations of reasoning.P. N. Johnson-Laird - 2002 - Thinking and Reasoning 8 (1):69 – 95.
    This paper describes Peirce's systems of logic diagrams, focusing on the so-called ''existential'' graphs, which are equivalent to the first-order predicate calculus. It analyses their implications for the nature of mental representations, particularly mental models with which they have many characteristics in common. The graphs are intended to be iconic, i.e., to have a structure analogous to the structure of what they represent. They have emergent logical consequences and a single graph can capture all the different ways in which a (...)
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  • Illusory inferences: a novel class of erroneous deductions.P. N. Johnson-Laird & Fabien Savary - 1999 - Cognition 71 (3):191-229.
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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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  • A computational framework for understanding the roles of simplicity and rational support in people's behavior explanations.Alan Jern, Austin Derrow-Pinion & A. J. Piergiovanni - 2021 - Cognition 210 (C):104606.
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  • Why contextual preference reversals maximize expected value.Andrew Howes, Paul A. Warren, George Farmer, Wael El-Deredy & Richard L. Lewis - 2016 - Psychological Review 123 (4):368-391.
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  • Utility Maximization and Bounds on Human Information Processing.Andrew Howes, Richard L. Lewis & Satinder Singh - 2014 - Topics in Cognitive Science 6 (2):198-203.
    Utility maximization is a key element of a number of theoretical approaches to explaining human behavior. Among these approaches are rational analysis, ideal observer theory, and signal detection theory. While some examples of these approaches define the utility maximization problem with little reference to the bounds imposed by the organism, others start with, and emphasize approaches in which bounds imposed by the information processing architecture are considered as an explicit part of the utility maximization problem. These latter approaches are the (...)
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  • Rational adaptation under task and processing constraints: Implications for testing theories of cognition and action.Andrew Howes, Richard L. Lewis & Alonso Vera - 2009 - Psychological Review 116 (4):717-751.
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  • Predicting Short‐Term Remembering as Boundedly Optimal Strategy Choice.Andrew Howes, Geoffrey B. Duggan, Kiran Kalidindi, Yuan-Chi Tseng & Richard L. Lewis - 2016 - Cognitive Science 40 (5):1192-1223.
    It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to it. The (...)
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  • Pragmatic reasoning with a point of view.Keith J. Holyoak & Patricia W. Cheng - 1995 - Thinking and Reasoning 1 (4):289 – 313.
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  • The social sciences needs more than integrative experimental designs: We need better theories.Moshe Hoffman, Tadeg Quillien & Bethany Burum - 2024 - Behavioral and Brain Sciences 47:e47.
    Almaatouq et al.'s prescription for more integrative experimental designs is welcome but does not address an equally important problem: Lack of adequate theories. We highlight two features theories ought to satisfy: “Well-specified” and “grounded.” We discuss the importance of these features, some positive exemplars, and the complementarity between the target article's prescriptions and improved theorizing.
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  • Chains of Inferences and the New Paradigm in the Psychology of Reasoning.Ulf Hlobil - 2016 - Review of Philosophy and Psychology 7 (1):1-16.
    The new paradigm in the psychology of reasoning draws on Bayesian formal frameworks, and some advocates of the new paradigm think of these formal frameworks as providing a computational-level theory of rational human inference. I argue that Bayesian theories should not be seen as providing a computational-level theory of rational human inference, where by “Bayesian theories” I mean theories that claim that all rational credal states are probabilistically coherent and that rational adjustments of degrees of belief in the light of (...)
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