113 found
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  1.  10
    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.  7
    Thomas L. Griffiths, Nick Chater, Charles Kemp, Amy Perfors & Joshua B. Tenenbaum (2010). Probabilistic Models of Cognition: Exploring Representations and Inductive Biases. Trends in Cognitive Sciences 14 (8):357-364.
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  3.  11
    Mike Oaksford & Nick Chater (1991). Against Logicist Cognitive Science. Mind and Language 6 (1):1-38.
  4.  23
    Morten H. Christiansen & Nick Chater (2008). Language as Shaped by the Brain. Behavioral and Brain Sciences 31 (5):489-509.
    It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes of language change (...)
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  5.  34
    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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  6.  17
    Nick Chater & Christopher D. Manning (2006). Probabilistic Models of Language Processing and Acquisition. Trends in Cognitive Sciences 10 (7):335-344.
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  7.  62
    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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  8.  19
    Nick Chater & Alan Yuille (2006). Probabilistic Models of Cognition: Conceptual Foundations. Trends in Cognitive Sciences 10 (7):287-291.
    Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, ‘sophisticated’ probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore (...)
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  9.  20
    Nick Chater & Mike Oaksford (1990). Autonomy, Implementation and Cognitive Architecture: A Reply to Fodor and Pylyshyn. Cognition 34 (1):93-107.
  10. Nick Chater & P. Vitanyi (2003). Simplicity: A Unifying Principle in Cognitive Science? Trends in Cognitive Sciences 7 (1):19-22.
  11.  4
    Morten H. Christiansen & Nick Chater (1999). Toward a Connectionist Model of Recursion in Human Linguistic Performance. Cognitive Science 23 (2):157-205.
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  12.  3
    Martin Redington, Nick Chater & Steven Finch (1998). Distributional Information: A Powerful Cue for Acquiring Syntactic Categories. Cognitive Science 22 (4):425-469.
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  13.  14
    Padraic Monaghan, Nick Chater & Morten H. Christiansen (2005). The Differential Role of Phonological and Distributional Cues in Grammatical Categorisation. Cognition 96 (2):143-182.
  14.  2
    Mike Oaksford & Nick Chater (2013). Dynamic Inference and Everyday Conditional Reasoning in the New Paradigm. Thinking and Reasoning 19 (3-4):346-379.
  15.  3
    Jennifer B. Misyak, Tigran Melkonyan, Hossam Zeitoun & Nick Chater (2014). Unwritten Rules: Virtual Bargaining Underpins Social Interaction, Culture, and Society. Trends in Cognitive Sciences 18 (10):512-519.
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  16.  7
    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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  17.  1
    Nick Chater (2015). Can Cognitive Science Create a Cognitive Economics? Cognition 135:52-55.
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  18.  20
    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 (...)
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  19.  5
    Katya Tentori, Nick Chater & Vincenzo Crupi (2015). Judging the Probability of Hypotheses Versus the Impact of Evidence: Which Form of Inductive Inference Is More Accurate and Time‐Consistent? Cognitive Science 39 (8).
    Inductive reasoning requires exploiting links between evidence and hypotheses. This can be done focusing either on the posterior probability of the hypothesis when updated on the new evidence or on the impact of the new evidence on the credibility of the hypothesis. But are these two cognitive representations equally reliable? This study investigates this question by comparing probability and impact judgments on the same experimental materials. The results indicate that impact judgments are more consistent in time and more accurate than (...)
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  20.  23
    Nick Chater & Morten H. Christiansen (2010). Language Acquisition Meets Language Evolution. Cognitive Science 34 (7):1131-1157.
    Recent research suggests that language evolution is a process of cultural change, in which linguistic structures are shaped through repeated cycles of learning and use by domain-general mechanisms. This paper draws out the implications of this viewpoint for understanding the problem of language acquisition, which is cast in a new, and much more tractable, form. In essence, the child faces a problem of induction, where the objective is to coordinate with others (C-induction), rather than to model the structure of the (...)
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  21.  2
    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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  22.  1
    Ivo Vlaev, Nick Chater, Neil Stewart & Gordon D. A. Brown (2011). Does the Brain Calculate Value? Trends in Cognitive Sciences 15 (11):546-554.
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  23.  5
    Ulrike Hahn, Nick Chater & Lucy B. Richardson (2003). Similarity as Transformation. Cognition 87 (1):1-32.
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  24.  21
    Anne S. Hsu & Nick Chater (2010). The Logical Problem of Language Acquisition: A Probabilistic Perspective. Cognitive Science 34 (6):972-1016.
    Natural language is full of patterns that appear to fit with general linguistic rules but are ungrammatical. There has been much debate over how children acquire these “linguistic restrictions,” and whether innate language knowledge is needed. Recently, it has been shown that restrictions in language can be learned asymptotically via probabilistic inference using the minimum description length (MDL) principle. Here, we extend the MDL approach to give a simple and practical methodology for estimating how much linguistic data are required to (...)
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  25.  3
    Emmanuel M. Pothos & Nick Chater (2002). A Simplicity Principle in Unsupervised Human Categorization. Cognitive Science 26 (3):303-343.
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  26.  5
    Martin Redington & Nick Chater (1996). Transfer in Artificial Grammar Learning: A Reevaluation. Journal of Experimental Psychology: General 125 (2):123.
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  27.  2
    Morten H. Christiansen & Nick Chater (1999). Connectionist Natural Language Processing: The State of the Art. Cognitive Science 23 (4):417-437.
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  28.  6
    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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  29. Susan Hurley & Nick Chater (eds.) (2005). Perspectives on Imitation: From Mirror Neurons to Memes, Vol II. MIT Press.
  30.  3
    Nick Chater & Gordon D. A. Brown (2008). From Universal Laws of Cognition to Specific Cognitive Models. Cognitive Science 32 (1):36-67.
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  31.  4
    Andrea Baronchelli, Ramon Ferrer-I.-Cancho, Romualdo Pastor-Satorras, Nick Chater & Morten H. Christiansen (2013). Networks in Cognitive Science. Trends in Cognitive Sciences 17 (7):348-360.
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  32.  3
    Anne S. Hsu, Nick Chater & Paul M. B. Vitányi (2011). The Probabilistic Analysis of Language Acquisition: Theoretical, Computational, and Experimental Analysis. Cognition 120 (3):380-390.
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  33.  82
    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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  34.  10
    Morten H. Christiansen & Nick Chater (2001). Connectionist Psycholinguistics: Capturing the Empirical Data. Trends in Cognitive Sciences 5 (2):82-88.
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  35. Ramsey M. Raafat, Nick Chater & Chris Frith (2009). Herding in Humans. Trends in Cognitive Sciences 13 (10):420-428.
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  36. Ulrike Hahn & Nick Chater (1998). Similarity and Rules: Distinct? Exhaustive? Empirically Distinguishable? Cognition 65 (2-3):197-230.
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  37. 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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  38.  24
    Mike Oaksford & Nick Chater (2003). Conditional Probability and the Cognitive Science of Conditional Reasoning. Mind and Language 18 (4):359–379.
  39.  3
    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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  40.  4
    Martin Redington & Nick Chater (1997). Probabilistic and Distributional Approaches to Language Acquisition. Trends in Cognitive Sciences 1 (7):273-281.
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  41.  31
    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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  42.  2
    Nick Chater, Joshua B. Tenenbaum & Alan Yuille (2006). Probabilistic Models of Cognition: Where Next? Trends in Cognitive Sciences 10 (7):292-293.
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  43.  37
    Nick Chater & Cecilia M. Heyes (1994). Animal Concepts: Content and Discontent. Mind and Language 9 (3):209-246.
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  44.  9
    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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  45.  17
    M. H. Christiansen & Nick Chater (1994). Generalization and Connectionist Language Learning. Mind and Language 9 (3):273-87.
  46.  5
    Morten H. Christiansen & Nick Chater (forthcoming). The Now-or-Never Bottleneck: A Fundamental Constraint on Language. Behavioral and Brain Sciences:1-52.
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  47. Nick Chater (2009). Rational and Mechanistic Perspectives on Reinforcement Learning. Cognition 113 (3):350-364.
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  48.  1
    Nick Chater (1993). Categorization, Theories and Folk Psychology. Behavioral and Brain Sciences 16 (1):37.
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  49.  71
    Martin J. Pickering & Nick Chater (1995). Why Cognitive Science is Not Formalized Folk Psychology. Minds and Machines 5 (3):309-337.
    It is often assumed that cognitive science is built upon folk psychology, and that challenges to folk psychology are therefore challenges to cognitive science itself. We argue that, in practice, cognitive science and folk psychology treat entirely non-overlapping domains: cognitive science considers aspects of mental life which do not depend on general knowledge, whereas folk psychology considers aspects of mental life which do depend on general knowledge. We back up our argument on theoretical grounds, and also illustrate the separation between (...)
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  50.  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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