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Mike Oaksford [72]M. Oaksford [6]Michael R. Oaksford [1]
  1.  12
    Mike Oaksford & Nick Chater (2007). Bayesian Rationality: The Probabilistic Approach to Human Reasoning. OUP Oxford.
    Are people rational? This question was central to Greek thought and has been at the heart of psychology and philosophy for millennia. This book provides a radical and controversial reappraisal of conventional wisdom in the psychology of reasoning, proposing that the Western conception of the mind as a logical system is flawed at the very outset. It argues that cognition should be understood in terms of probability theory, the calculus of uncertain reasoning, rather than in terms of logic, the calculus (...)
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  2.  13
    Mike Oaksford & Nick Chater (1991). Against Logicist Cognitive Science. Mind and Language 6 (1):1-38.
  3.  1
    Nicole Cruz, Jean Baratgin, Mike Oaksford & David E. Over (2015). Bayesian Reasoning with Ifs and Ands and Ors. Frontiers in Psychology 6.
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  4.  1
    Mike Oaksford (2015). Imaging Deductive Reasoning and the New Paradigm. Frontiers in Human Neuroscience 9.
  5.  77
    Mike Oaksford & Nick Chater (2009). Précis of Bayesian Rationality: The Probabilistic Approach to Human Reasoning. 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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  6.  40
    Nick Chater & Mike Oaksford (eds.) (2008). The Probabilistic Mind: Prospects for Bayesian Cognitive Science. OUP Oxford.
    'The Probabilistic Mind' is a follow-up to the influential and highly cited 'Rational Models of Cognition' . It brings together developments in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods.
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  7.  23
    Nick Chater & Mike Oaksford (1990). Autonomy, Implementation and Cognitive Architecture: A Reply to Fodor and Pylyshyn. Cognition 34 (1):93-107.
  8.  6
    M. Oaksford & N. Chater (eds.) (2010). Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press.
    This book shows how these developments have led researchers to view people's conditional reasoning behaviour more as succesful probabilistic reasoning rather ...
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  9.  7
    Mike Oaksford & Nick Chater (2013). Dynamic Inference and Everyday Conditional Reasoning in the New Paradigm. Thinking and Reasoning 19 (3-4):346-379.
  10.  8
    Nilufa Ali, Nick Chater & Mike Oaksford (2011). The Mental Representation of Causal Conditional Reasoning: Mental Models or Causal Models. Cognition 119 (3):403-418.
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  11.  1
    Mike Oaksford (1993). Mental Models and the Tractability of Everyday Reasoning. Behavioral and Brain Sciences 16 (2):360.
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  12. M. Oaksford & N. Chater (eds.) (1998). Rational Models of Cognition. Oxford University Press Uk.
    This book explores a new approach to understanding the human mind - rational analysis - that regards thinking as a facility adapted to the structure of the world. This approach is most closely associated with the work of John R Anderson, who published the original book on rational analysis in 1990. Since then, a great deal of work has been carried out in a number of laboratories around the world, and the aim of this book is to bring this work (...)
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  13.  49
    Ulrike Hahn & Mike Oaksford (2006). A Bayesian Approach to Informal Argument Fallacies. Synthese 152 (2):207 - 236.
    We examine in detail three classic reasoning fallacies, that is, supposedly ``incorrect'' forms of argument. These are the so-called argumentam ad ignorantiam, the circular argument or petitio principii, and the slippery slope argument. In each case, the argument type is shown to match structurally arguments which are widely accepted. This suggests that it is not the form of the arguments as such that is problematic but rather something about the content of those examples with which they are typically justified. This (...)
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  14.  29
    Nick Chater & Mike Oaksford (2013). Programs as Causal Models: Speculations on Mental Programs and Mental Representation. Cognitive Science 37 (6):1171-1191.
    Judea Pearl has argued that counterfactuals and causality are central to intelligence, whether natural or artificial, and has helped create a rich mathematical and computational framework for formally analyzing causality. Here, we draw out connections between these notions and various current issues in cognitive science, including the nature of mental “programs” and mental representation. We argue that programs (consisting of algorithms and data structures) have a causal (counterfactual-supporting) structure; these counterfactuals can reveal the nature of mental representations. Programs can also (...)
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  15.  12
    M. Oaksford (2001). The Probabilistic Approach to Human Reasoning. Trends in Cognitive Sciences 5 (8):349-357.
    A recent development in the cognitive science of reasoning has been the emergence of a probabilistic approach to the behaviour observed on ostensibly logical tasks. According to this approach the errors and biases documented on these tasks occur because people import their everyday uncertain reasoning strategies into the laboratory. Consequently participants' apparently irrational behaviour is the result of comparing it with an inappropriate logical standard. In this article, we contrast the probabilistic approach with other approaches to explaining rationality, and then (...)
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  16.  8
    Nick Chater, Noah Goodman, Thomas L. Griffiths, Charles Kemp, Mike Oaksford & Joshua B. Tenenbaum (2011). The Imaginary Fundamentalists: The Unshocking Truth About Bayesian Cognitive Science. Behavioral and Brain Sciences 34 (4):194-196.
    If Bayesian Fundamentalism existed, Jones & Love's (J&L's) arguments would provide a necessary corrective. But it does not. Bayesian cognitive science is deeply concerned with characterizing algorithms and representations, and, ultimately, implementations in neural circuits; it pays close attention to environmental structure and the constraints of behavioral data, when available; and it rigorously compares multiple models, both within and across papers. J&L's recommendation of Bayesian Enlightenment corresponds to past, present, and, we hope, future practice in Bayesian cognitive science.
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  17.  3
    Mike Oaksford (2013). Quantum Probability, Intuition, and Human Rationality. Behavioral and Brain Sciences 36 (3):303-303.
    This comment suggests that Pothos & Busmeyer (P&B) do not provide an intuitive rational foundation for quantum probability (QP) theory to parallel standard logic and classical probability (CP) theory. In particular, the intuitive foundation for standard logic, which underpins CP, is the elimination of contradictions – that is, believing p and not-p is bad. Quantum logic, which underpins QP, explicitly denies non-contradiction, which seems deeply counterintuitive for the macroscopic world about which people must reason. I propose a possible resolution in (...)
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  18.  19
    Nick Chater & Mike Oaksford (1999). Ten Years of the Rational Analysis of Cognition. Trends in Cognitive Sciences 3 (2):57-65.
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  19.  9
    Mike Oaksford & Nick Chater (2014). Probabilistic Single Function Dual Process Theory and Logic Programming as Approaches to Non-Monotonicity in Human Vs. Artificial Reasoning. Thinking and Reasoning 20 (2):269-295.
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  20.  11
    Mike Oaksford & Nick Chater (2012). Dual Processes, Probabilities, and Cognitive Architecture. 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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  21.  31
    Mike Oaksford & Nick Chater (2003). Conditional Probability and the Cognitive Science of Conditional Reasoning. Mind and Language 18 (4):359–379.
  22.  97
    Nick Chater & Mike Oaksford (2000). The Rational Analysis of Mind and Behavior. Synthese 122 (1-2):93-131.
    Rational analysis (Anderson 1990, 1991a) is an empiricalprogram of attempting to explain why the cognitive system isadaptive, with respect to its goals and the structure of itsenvironment. We argue that rational analysis has two importantimplications for philosophical debate concerning rationality. First,rational analysis provides a model for the relationship betweenformal principles of rationality (such as probability or decisiontheory) and everyday rationality, in the sense of successfulthought and action in daily life. Second, applying the program ofrational analysis to research on human reasoning (...)
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  23. Ulrike Hahn & Mike Oaksford (2007). The Rationality of Informal Argumentation: A Bayesian Approach to Reasoning Fallacies. Psychological Review 114 (3):704-732.
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  24.  7
    Masasi Hattori & Mike Oaksford (2007). Adaptive Non‐Interventional Heuristics for Covariation Detection in Causal Induction: Model Comparison and Rational Analysis. Cognitive Science 31 (5):765-814.
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  25.  30
    Ulrike Hahn & Mike Oaksford (2007). The Burden of Proof and Its Role in Argumentation. Argumentation 21 (1):39-61.
    The notion of “the burden of proof” plays an important role in real-world argumentation contexts, in particular in law. It has also been given a central role in normative accounts of argumentation, and has been used to explain a range of classic argumentation fallacies. We argue that in law the goal is to make practical decisions whereas in critical discussion the goal is frequently simply to increase or decrease degree of belief in a proposition. In the latter case, it is (...)
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  26. Mike Oaksford & Nick Chater (2007). Bayesian Rationality: The Probabilistic Approach to Human Reasoning. Oxford University Press Uk.
    Are people rational? This question was central to Greek thought; and has been at the heart of psychology and philosophy for millennia. This book provides a radical and controversial reappraisal of conventional wisdom in the psychology of reasoning, proposing that the Western conception of the mind as a logical system is flawed at the very outset. It argues that cognition should be understood in terms of probability theory, the calculus of uncertain reasoning, rather than in terms of logic, the calculus (...)
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  27.  33
    Mike Oaksford & Nick Chater (2009). The Uncertain Reasoner: Bayes, Logic, and Rationality. 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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  28.  1
    Mike Oaksford & Nick Chater (2008). Probability Logic and the Modus Ponens-Modus Tollens Asymmetry in Conditional Inference. In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. OUP Oxford 97--120.
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  29.  13
    Jean Baratgin, Igor Douven, Jonathan StB. T. Evans, Mike Oaksford, David Over & Guy Politzer (2015). The New Paradigm and Mental Models. Trends in Cognitive Sciences 19 (10):547-548.
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  30.  14
    Mike Oaksford & Nick Chater (2001). The Probabilistic Approach to Human Reasoning. Trends in Cognitive Sciences 5 (8):349-357.
    A recent development in the cognitive science of reasoning has been the emergence of a probabilistic approach to the behaviour observed on ostensibly logical tasks. According to this approach the errors and biases documented on these tasks occur because people import their everyday uncertain reasoning strategies into the laboratory. Consequently participants' apparently irrational behaviour is the result of comparing it with an inappropriate logical standard. In this article, we contrast the probabilistic approach with other approaches to explaining rationality, and then (...)
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  31.  7
    Nick Perham & Mike Oaksford (2005). Deontic Reasoning With Emotional Content: Evolutionary Psychology or Decision Theory? Cognitive Science 29 (5):681-718.
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  32.  5
    M. Oaksford (1995). Information Gain Explains Relevance Which Explains the Selection Task. Cognition 57 (1):97-108.
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  33.  20
    Mike Oaksford, Nick Chater & Becki Grainger (1999). Probabilistic Effects in Data Selection. 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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  34.  15
    Ulrike Hahn, Adam J. L. Harris & Mike Oaksford (2013). Rational Argument, Rational Inference. Argument and Computation 4 (1):21 - 35.
    (2013). Rational argument, rational inference. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 21-35. doi: 10.1080/19462166.2012.689327.
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  35.  5
    Mike Oaksford & Nick Chater (2016). Probabilities, Causation, and Logic Programming in Conditional Reasoning: Reply to Stenning and Van Lambalgen. 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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  36. Mike Oaksford & Nick Chater (1994). A Rational Analysis of the Selection Task as Optimal Data Selection. Psychological Review 101 (4):608-631.
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  37.  16
    Nick Chater & Mike Oaksford (1993). Logicism, Mental Models and Everyday Reasoning: Reply to Garnham. Mind and Language 8 (1):72-89.
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  38.  2
    Ulrike Hahn & Mike Oaksford (2006). A Bayesian Approach to Informal Argument Fallacies. Synthese 152 (2):207-236.
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  39.  16
    Mike Oaksford & Ulrike Hahn (2006). Non-Monotonicity and Informal Reasoning: Comment on Ferguson (2003). Argumentation 20 (2):245-251.
    In this paper, it is argued that Ferguson’s (2003, Argumentation 17, 335–346) recent proposal to reconcile monotonic logic with defeasibility has three counterintuitive consequences. First, the conclusions that can be derived from his new rule of inference are vacuous, a point that as already made against default logics when there are conflicting defaults. Second, his proposal requires a procedural “hack” to the break the symmetry between the disjuncts of the tautological conclusions to which his proposal leads. Third, Ferguson’s proposal amounts (...)
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  40.  6
    Nilufa Ali, Anne Schlottmann, Abigail Shaw, Nick Chater & Mike Oaksford (2010). Causal Discounting and Conditional Reasoning in Children. In M. Oaksford & N. Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press
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  41.  13
    Nick Chater & Mike Oaksford (2011). Local and Global Inferential Relations: Response to Over (2009). Thinking and Reasoning 15 (4):439-446.
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  42.  7
    Nick Chater & Mike Oaksford (2011). Local and Global Inferential Relations: Response to Over (2009). Thinking and Reasoning 15 (4):439-446.
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  43.  3
    Mike Oaksford & Nick Chater (2011). The “is-Ought Fallacy” Fallacy. 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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  44.  6
    Ruth Mj Byrne, Philip N. Johnson-Laird, M. Oaksford & N. Chater (2010). Conditionals and Possibilities. In M. Oaksford & N. Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press
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  45.  9
    Ulrike Hahn & Mike Oaksford (2008). A Normative Theory of Argument Strength. Informal Logic 26 (1):1-24.
    In this article, we argue for the general importance of normative theories of argument strength. We also provide some evidence based on our recent work on the fallacies as to why Bayesian probability might, in fact, be able to supply such an account. In the remainder of the article we discuss the general characteristics that make a specifically Bayesian approach desirable, and critically evaluate putative flaws of Bayesian probability that have been raised in the argumentation literature.
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  46.  37
    Mike Oaksford, Nick Chater & Keith Stenning (1990). Connectionism, Classical Cognitive Science and Experimental Psychology. AI and Society 4 (1):73-90.
    Classical symbolic computational models of cognition are at variance with the empirical findings in the cognitive psychology of memory and inference. Standard symbolic computers are well suited to remembering arbitrary lists of symbols and performing logical inferences. In contrast, human performance on such tasks is extremely limited. Standard models donot easily capture content addressable memory or context sensitive defeasible inference, which are natural and effortless for people. We argue that Connectionism provides a more natural framework in which to model this (...)
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  47.  2
    Mike Oaksford & Mike Malloch (1993). Computational and Biological Constraints in the Psychology of Reasoning. Behavioral and Brain Sciences 16 (3):468.
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  48. Nick Chater, Mike Oaksford, Ramin Nakisa & Martin Redington (2003). Fast, Frugal, and Rational: How Rational Norms Explain Behavior. Organizational Behavior and Human Decision Processes 90 (1):63-86.
    Much research on judgment and decision making has focussed on the adequacy of classical rationality as a description of human reasoning. But more recently it has been argued that classical rationality should also be rejected even as normative standards for human reasoning. For example, Gigerenzer and Goldstein and Gigerenzer and Todd argue that reasoning involves “fast and frugal” algorithms which are not justified by rational norms, but which succeed in the environment. They provide three lines of argument for this view, (...)
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  49. Mike Oaksford & Nick Chater (1996). Rational Explanation of the Selection Task. Psychological Review 103 (2):381-391.
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  50.  14
    Mike Oaksford & Nick Chater (1995). Two and Three Stage Models of Deontic Reasoning. Thinking and Reasoning 1 (4):350 – 357.
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