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John Anderson [120]John R. Anderson [40]John M. Anderson [16]John J. Anderson [5]
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Profile: John Anderson (Mississippi College)
  1.  41
    John R. Anderson (2007). How Can the Human Mind Occur in the Physical Universe? OUP Usa.
    The human cognitive architecture consists of a set of largely independent modules associated with different brain regions. This book discusses in detail how these various modules can combine to produce behaviours as varied as driving a car and solving an algebraic equation.
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  2. John R. Anderson (1991). Is Human Cognition Adaptive? Behavioral and Brain Sciences 14 (3):471-485.
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  3.  5
    John R. Anderson (2005). Human Symbol Manipulation Within an Integrated Cognitive Architecture. Cognitive Science 29 (3):313-341.
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  4.  52
    John R. Anderson (1978). Arguments Concerning Representations for Mental Imagery. Psychological Review.
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  5.  3
    John R. Anderson (1987). Methodologies for Studying Human Knowledge. Behavioral and Brain Sciences 10 (3):467.
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  6.  2
    Niels A. Taatgen & John R. Anderson (2002). Why Do Children Learn to Say “Broke”? A Model of Learning the Past Tense Without Feedback. Cognition 86 (2):123-155.
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  7.  6
    Lynne M. Reder, John R. Anderson & Robert A. Bjork (1974). A Semantic Interpretation of Encoding Specificity. Journal of Experimental Psychology 102 (4):648-656.
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  8.  3
    John R. Anderson, Cameron S. Carter, Jon M. Fincham, Yulin Qin, Susan M. Ravizza & Miriam Rosenberg‐Lee (2008). Using fMRI to Test Models of Complex Cognition. Cognitive Science 32 (8):1323-1348.
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  9.  19
    Niels Taatgen & John R. Anderson (2010). The Past, Present, and Future of Cognitive Architectures. Topics in Cognitive Science 2 (4):693-704.
    Cognitive architectures are theories of cognition that try to capture the essential representations and mechanisms that underlie cognition. Research in cognitive architectures has gradually moved from a focus on the functional capabilities of architectures to the ability to model the details of human behavior, and, more recently, brain activity. Although there are many different architectures, they share many identical or similar mechanisms, permitting possible future convergence. In judging the quality of a particular cognitive model, it is pertinent to not just (...)
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  10.  3
    John R. Anderson (2002). Spanning Seven Orders of Magnitude: A Challenge for Cognitive Modeling. Cognitive Science 26 (1):85-112.
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  11.  4
    John R. Anderson, Jon M. Fincham, Yulin Qin & Andrea Stocco (2008). A Central Circuit of the Mind. Trends in Cognitive Sciences 12 (4):136-143.
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  12.  8
    John R. Anderson & Jon M. Fincham (2014). Discovering the Sequential Structure of Thought. Cognitive Science 38 (2):322-352.
    Multi-voxel pattern recognition techniques combined with Hidden Markov models can be used to discover the mental states that people go through in performing a task. The combined method identifies both the mental states and how their durations vary with experimental conditions. We apply this method to a task where participants solve novel mathematical problems. We identify four states in the solution of these problems: Encoding, Planning, Solving, and Respond. The method allows us to interpret what participants are doing on individual (...)
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  13.  20
    John R. Anderson & Christian Lebiere (2003). The Newell Test for a Theory of Cognition. Behavioral and Brain Sciences 26 (5):587-601.
    Newell proposed that cognitive theories be developed in an effort to satisfy multiple criteria and to avoid theoretical myopia. He provided two overlapping lists of 13 criteria that the human cognitive architecture would have to satisfy in order to be functional. We have distilled these into 12 criteria: flexible behavior, real-time performance, adaptive behavior, vast knowledge base, dynamic behavior, knowledge integration, natural language, learning, development, evolution, and brain realization. There would be greater theoretical progress if we evaluated theories by a (...)
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  14.  5
    John R. Anderson & Lynne M. Reder (1999). The Fan Effect: New Results and New Theories. Journal of Experimental Psychology: General 128 (2):186.
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  15.  3
    Kenneth R. Koedinger & John R. Anderson (1990). Abstract Planning and Perceptual Chunks: Elements of Expertise in Geometry. Cognitive Science 14 (4):511-550.
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  16.  4
    Raluca Budiu & John R. Anderson (2004). Interpretation‐Based Processing: A Unified Theory of Semantic Sentence Comprehension. Cognitive Science 28 (1):1-44.
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  17. John Anderson (1932). Utilitarianism. Australasian Journal of Philosophy 10 (3):161 – 172.
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  18.  5
    Marsha C. Lovett & John R. Anderson (2005). Thinking as a Production System. In K. Holyoak & B. Morrison (eds.), The Cambridge Handbook of Thinking and Reasoning. Cambridge Univ Pr 401--429.
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  19.  3
    Dario D. Salvucci & John R. Anderson (2001). Integrating Analogical Mapping and General Problem Solving: The Path‐Mapping Theory. Cognitive Science 25 (1):67-110.
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  20.  6
    Myeong-Ho Sohn & John R. Anderson (2001). Task Preparation and Task Repetition: Two-Component Model of Task Switching. Journal of Experimental Psychology: General 130 (4):764.
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  21.  10
    John J. Anderson (1957). The Sane Society. New Scholasticism 31 (2):274-278.
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  22.  3
    John R. Anderson, Robert Farrell & Ron Sauers (1984). Learning to Program in LISP1. Cognitive Science 8 (2):87-129.
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  23.  75
    John P. Anderson (1997). Sophie's Choice. Southern Journal of Philosophy 35 (4):439-450.
  24.  3
    Philip I. Pavlik & John R. Anderson (2005). Practice and Forgetting Effects on Vocabulary Memory: An Activation‐Based Model of the Spacing Effect. Cognitive Science 29 (4):559-586.
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  25.  5
    John R. Anderson, Frederick G. Conrad & Albert T. Corbett (1989). Skill Acquisition and the LISP Tutor. Cognitive Science 13 (4):467-505.
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  26.  66
    John R. Anderson (1984). The Development of Self-Recognition: A Review. Developmental Psychobiology 17:35-49.
  27.  13
    John Anderson (1962). Studies in Empirical Philosophy. [Sydney]Angus and Robertson.
  28.  7
    Christian Lebière, John R. Anderson & Lynne M. Reder (1994). Error Modeling in the ACT-R Production System. In Ashwin Ram & Kurt Eiselt (eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. Erlbaum 555--559.
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  29.  30
    John R. Anderson, Christian Lebiere, Marsha Lovett & Lynne Reder (1998). ACT-R: A Higher-Level Account of Processing Capacity. Behavioral and Brain Sciences 21 (6):831-832.
    We present an account of processing capacity in the ACT-R theory. At the symbolic level, the number of chunks in the current goal provides a measure of relational complexity. At the subsymbolic level, limits on spreading activation, measured by the attentional parameter W, provide a theory of processing capacity, which has been applied to performance, learning, and individual differences data.
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  30.  9
    John Anderson (forthcoming). A Generic Distributed Simulation System for Intelligent Agent Design and Evaluation. Proceedings of the Tenth Conference on Ai, Simulation and Planning, Ais-2000, Society for Computer Simulation International.
  31. John R. Anderson (1977). Induction of Augmented Transition Networks. Cognitive Science 1 (2):125-157.
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  32.  1
    John Anderson (1980). Education and Inquiry. Barnes & Noble Books.
  33.  2
    Hee Seung Lee, Shawn Betts & John R. Anderson (2015). Learning Problem‐Solving Rules as Search Through a Hypothesis Space. Cognitive Science 40 (1):n/a-n/a.
    Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem property such as computational difficulty of the rules biased the search process and so affected learning. Experiment 2 examined the impact of examples as instructional tools (...)
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  34.  5
    John Anderson & Jacky Baltes (forthcoming). Agent-Based Control in a Global-Vision Robotic Soccer Team. Proceedings of the Agents Meet Robots Workshop, 17th Conference of the Canadian Society for the Computational Studies of Intelligence (Ai-04).
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  35.  3
    John Anderson (1945). Ii. The One Good. Australasian Journal of Philosophy 23 (1-3):85 – 89.
  36.  3
    John E. Anderson (1920). Intelligence Tests of Yale Freshmen. Journal of Philosophy, Psychology and Scientific Methods 17 (17):469-469.
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  37.  3
    John Anderson (1931). The Book of Diogenes Laertius: Its Spirit and its Method. [REVIEW] Australasian Journal of Philosophy 9:71.
  38.  4
    John Anderson (1926). Propositions and Judgments. Mind 35 (138):237-241.
  39.  2
    Robert L. Goldstone, John R. Anderson, Nick Chater, Andy Clark, Shimon Edelman, Kenneth Forbus, Dedre Gentner, Raymond W. Gibbs Jr, James Greeno & Robert A. Jacobs (2004). Journal of The Cognitive Science Society. Cognitive Science 28 (3).
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  40.  43
    John Anderson (1931). Socrates as an Educator. Australasian Journal of Philosophy 9 (3):172 – 184.
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  41.  4
    John Anderson (1926). Discussions: The Truth of Propositions. Mind 35 (140):237-241.
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  42.  17
    John Anderson (1938). The Problem of Causality. Australasian Journal of Philosophy 16 (2):127 – 142.
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  43.  34
    John Anderson (1933). Realism Versus Relativism in Ethics. Australasian Journal of Philosophy 11 (1):1 – 11.
    This article analyzes the central weaknesses of both relativism and traditional empiricism as overarching accounts of science appropriate for psychology. A third approach, a variant of scientific realism, is described and discussed, and it is argued that this approach avoids the most pernicious features of both relativism and empiricism. This version of scientific realism postulates that the rational structure of science is composed of four interlocked categories: aims, epistemic values, methodological rules, and theories. These categories are described, and the nature (...)
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  44.  34
    John Anderson (1936). The Cogito of Descartes. Australasian Journal of Philosophy 14 (1):48 – 68.
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  45.  2
    Christian D. Schunn & John R. Anderson (1999). The Generality/Specificity of Expertise in Scientific Reasoning. Cognitive Science 23 (3):337-370.
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  46.  9
    F. U. T. Aepinus, Archibald Alexander, Archibald Alison, John Anderson, Maria Rosa Antognazza, Thomas Aquinas, D. M. Armstrong, Antione Arnauld, J. L. Austin & Johann Sebastian Bach (2004). Index of Names and Subjects. In Terence Cuneo Rene van Woudenberg (ed.), The Cambridge Companion to Thomas Reid. Cambridge University Press 361.
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  47.  4
    John J. Anderson (1957). Scientific Humanism and Christian Thought. New Scholasticism 31 (4):586-587.
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  48.  7
    John Anderson, D. M. Armstrong & Dirk Baltzly (2007). Appearance in This List Neither Guarantees nor Precludes a Future Review of the Book. Mind 116:463.
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  49. John Mueller Anderson (1962). Natural Deduction. Belmont, Calif.,Wadsworth Pub. Co..
     
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  50.  6
    Scott A. Douglass & John R. Anderson (2008). A Model of Language Processing and Spatial Reasoning Using Skill Acquisition to Situate Action. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society 2281--2286.
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