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  1. Fernand Gobet (2014). William R. Uttal: Mind and Brain: A Critical Appraisal of Cognitive Neuroscience. [REVIEW] Minds and Machines 24 (2):221-226.
    The relation between mind and brain is one of the big scientific questions that has attracted scientists’ attention for centuries but also eluded their understanding. In this book, William Uttal provides a critical review of cognitive neuroscience, focusing on a specific question: What do the brain-imaging techniques developed in the last two decades or so—mostly functional magnetic resonance imaging (fMRI) and positron emission tomography (PET)—tell us about the brain-mind problem? His unambiguous and abrasive answer is: nothing.The book is organized in (...)
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  2. Fernand Gobet, Allan Snyder, Terry Bossomaier & Mike Harré (2014). Designing a €Œbetter” Brain: Insights From Experts and Savants. Frontiers in Psychology 5.
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  3. David Z. Hambrick, Erik M. Altmann, Frederick L. Oswald, Elizabeth J. Meinz & Fernand Gobet (2014). Facing Facts About Deliberate Practice. Frontiers in Psychology 5.
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  4. Julian M. Pine, Daniel Freudenthal, Grzegorz Krajewski & Fernand Gobet (2013). Do Young Children Have Adult-Like Syntactic Categories? Zipf's Law and the Case of the Determiner. Cognition 127 (3):345-360.
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  5. Yvan I. Russell & Fernand Gobet (2013). What is Counterintuitive? Religious Cognition and Natural Expectation. Review of Philosophy and Psychology 4 (4):715-749.
    What is ‘counterintuitive’? There is general agreement that it refers to a violation of previously held knowledge, but the precise definition seems to vary with every author and study. The aim of this paper is to deconstruct the notion of ‘counterintuitive’ and provide a more philosophically rigorous definition congruent with the history of psychology, recent experimental work in ‘minimally counterintuitive’ concepts, the science vs. religion debate, and the developmental and evolutionary background of human beings. We conclude that previous definitions of (...)
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  6. Fernand Gobet (2012). Concepts Without Intuition Lose the Game: Commentary on Montero and Evans (2011). [REVIEW] Phenomenology and the Cognitive Sciences 11 (2):237-250.
    In several papers, Hubert Dreyfus has used chess as a paradigmatic example of how experts act intuitively, rarely using deliberation when selecting actions, while individuals that are only competent rely on analytic and deliberative thought. By contrast, Montero and Evans (Phenomenology and the Cognitive Sciences 10:175–194, 2011 ) argue that intuitive aspects of chess are actually rational, in the sense that actions can be justified. In this paper, I show that both Dreyfus’s and Montero and Evans’s views are too extreme, (...)
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  7. Fernand Gobet, Peter McLeod & Merim Bilalić (2011). Expert and “Novice” Problem Solving Strategies in Chess: Sixty Years of Citing de Groot (1946). Thinking and Reasoning 14 (4):395-408.
    In a famous study of expert problem solving, de Groot (1946/1978) examined how chess players found the best move. He reported that there was little difference in the way that the best players (Grand Masters) and very good players (Candidate Masters) searched the board. Although this result has been regularly cited in studies of expertise, it is frequently misquoted. It is often claimed that de Groot found no difference in the way that experts and novices investigate a problem. Comparison of (...)
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  8. Merim Bilalić & Fernand Gobet (2009). They Do What They Are Told to Do: The Influence of Instruction on (Chess) Expert Perception—Commentary on Linhares and Brum (2007). Cognitive Science 33 (5):743-747.
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  9. Merim Bilalić, Peter McLeod & Fernand Gobet (2009). Specialization Effect and Its Influence on Memory and Problem Solving in Expert Chess Players. Cognitive Science 33 (6):1117-1143.
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  10. Fernand Gobet & Philippe Chassy (2009). Expertise and Intuition: A Tale of Three Theories. [REVIEW] Minds and Machines 19 (2):151-180.
    Several authors have hailed intuition as one of the defining features of expertise. In particular, while disagreeing on almost anything that touches on human cognition and artificial intelligence, Hubert Dreyfus and Herbert Simon agreed on this point. However, the highly influential theories of intuition they proposed differed in major ways, especially with respect to the role given to search and as to whether intuition is holistic or analytic. Both theories suffer from empirical weaknesses. In this paper, we show how, with (...)
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  11. Merim Bilalić, Peter McLeod & Fernand Gobet (2008). Why Good Thoughts Block Better Ones: The Mechanism of the Pernicious Einstellung (Set) Effect. Cognition 108 (3):652-661.
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  12. Fernand Gobet & Philippe Chassy (2008). Season of Birth and Chess Expertise. Journal of Biosocial Science 40 (2):313.
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  13. Gary Jones, Fernand Gobet & Julian M. Pine (2008). Computer Simulations of Developmental Change: The Contributions of Working Memory Capacity and Long‐Term Knowledge. Cognitive Science 32 (7):1148-1176.
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  14. Daniel Freudenthal, Julian M. Pine, Javier Aguado‐Orea & Fernand Gobet (2007). Modeling the Developmental Patterning of Finiteness Marking in English, Dutch, German, and Spanish Using MOSAIC. Cognitive Science 31 (2):311-341.
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  15. Enrique Frias-Martinez & Fernand Gobet (2007). Automatic Generation of Cognitive Theories Using Genetic Programming. Minds and Machines 17 (3):287-309.
    Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming (GP). Our approach evolves from experimental data cognitive theories that explain “the mental (...)
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  16. Daniel Freudenthal, Julian M. Pine & Fernand Gobet (2006). Modeling the Development of Children's Use of Optional Infinitives in Dutch and English Using MOSAIC. Cognitive Science 30 (2):277-310.
    In this study we use a computational model of language learning called model of syntax acquisition in children (MOSAIC) to investigate the extent to which the optional infinitive (OI) phenomenon in Dutch and English can be explained in terms of a resource-limited distributional analysis of Dutch and English child-directed speech. The results show that the same version of MOSAIC is able to simulate changes in the pattern of finiteness marking in 2 children learning Dutch and 2 children learning English as (...)
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  17. Fernand Gobet, Peter C. R. Lane, Steve Croker, Peter C.-H. Cheng, Gary Jones, Iain Oliver & Julian M. Pine (2001). Mechanisms in Human Learning. Trends in Cognitive Sciences 5 (6):236-243.
    Pioneering work in the 1940s and 1950s suggested that the concept of chunking might be important in many processes of perception, learning and cognition in humans and animals. We summarize here the major sources of evidence for chunking mechanisms, and consider how such mechanisms have been implemented in computational models of the learning process. We distinguish two forms of chunking: the first deliberate, under strategic control, and goal-oriented; the second automatic, continuous, and linked to perceptual processes. Recent work with discrimination-network (...)
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  18. Peter C. R. Lane, Peter C.-H. Cheng & Fernand Gobet (2001). The CHREST Model of Active Perception and its Role in Problem Solving. Behavioral and Brain Sciences 24 (5):892-893.
    We discuss the relation of the Theory of Event Coding (TEC) to a computational model of expert perception, CHREST, based on the chunking theory. TEC's status as a verbal theory leaves several questions unanswerable, such as the precise nature of internal representations used, or the degree of learning required to obtain a particular level of competence: CHREST may help answer such questions.
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  19. Peter C. R. Lane, Fernand Gobet & Peter C.-H. Cheng (2001). What Forms the Chunks in a Subject's Performance? Lessons From the CHREST Computational Model of Learning. Behavioral and Brain Sciences 24 (1):128-129.
    Computational models of learning provide an alternative technique for identifying the number and type of chunks used by a subject in a specific task. Results from applying CHREST to chess expertise support the theoretical framework of Cowan and a limit in visual short-term memory capacity of 3–4 looms. An application to learning from diagrams illustrates different identifiable forms of chunk.
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  20. Fernand Gobet & Herbert A. Simon (2000). Five Seconds or Sixty? Presentation Time in Expert Memory. Cognitive Science 24 (4):651-682.
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  21. Fernand Gobet (1998). Expert Memory: A Comparison of Four Theories. Cognition 66 (2):115-152.
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  22. Fernand Gobet (1997). A Pattern-Recognition Theory of Search in Expert Problem Solving. Thinking and Reasoning 3 (4):291 – 313.
    Understanding how look-ahead search and pattern recognition interact is one of the important research questions in the study of expert problem solving. This paper examines the implications of the template theory Gobet & Simon, 1996a , a recent theory of expert memory, on the theory of problem solving in chess. Templates are chunks Chase & Simon, 1973 that have evolved into more complex data structures and that possess slots allowing values to be encoded rapidly. Templates may facilitate search in three (...)
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