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  1. Problems of extension, representation, and computational irreducibility.Patrick Suppes - 1990 - Behavioral and Brain Sciences 13 (3):507-508.
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  • Connectionism and classical computation.Nick Chater - 1990 - Behavioral and Brain Sciences 13 (3):493-494.
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  • Keeping representations at bay.Stanley Munsat - 1990 - Behavioral and Brain Sciences 13 (3):502-503.
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  • How automatic are crossmodal correspondences?Charles Spence & Ophelia Deroy - 2013 - Consciousness and Cognition 22 (1):245-260.
    The last couple of years have seen a rapid growth of interest in the study of crossmodal correspondences – the tendency for our brains to preferentially associate certain features or dimensions of stimuli across the senses. By now, robust empirical evidence supports the existence of numerous crossmodal correspondences, affecting people’s performance across a wide range of psychological tasks – in everything from the redundant target effect paradigm through to studies of the Implicit Association Test, and from speeded discrimination/classification tasks through (...)
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  • Perspectives on Modeling in Cognitive Science.Richard M. Shiffrin - 2010 - Topics in Cognitive Science 2 (4):736-750.
    This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author’s personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and for many, bewildering. Yet to come to anything approaching adequate insights into the infinitely complex fields of mind, brain, and intelligent (...)
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  • Straw-men and selective citation are needed to argue that associative-link formation makes no contribution to human learning.Dominic M. Dwyer, Michael E. Le Pelley, David N. George, Mark Haselgrove & Robert C. Honey - 2009 - Behavioral and Brain Sciences 32 (2):206-207.
    Mitchell et al. contend that there is no need to posit a contribution based on the formation of associative links to human learning. In order to sustain this argument, they have ignored evidence which is difficult to explain with propositional accounts; and they have mischaracterised the evidence they do cite by neglecting features of these experiments that contradict a propositional account.
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  • A new approach to the formulation and testing of learning models.Joseph F. Hanna - 1966 - Synthese 16 (3-4):344 - 380.
    It is argued that current attempts to model human learning behavior commonly fail on one of two counts: either the model assumptions are artificially restricted so as to permit the application of mathematical techniques in deriving their consequences, or else the required complex assumptions are imbedded in computer programs whose technical details obscure the theoretical content of the model. The first failing is characteristic of so-called mathematical models of learning, while the second is characteristic of computer simulation models. An approach (...)
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  • Elemental representations of stimuli in associative learning.Justin A. Harris - 2006 - Psychological Review 113 (3):584-605.
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  • Connectionist models: Too little too soon?William Timberlake - 1990 - Behavioral and Brain Sciences 13 (3):508-509.
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  • But what is the substance of connectionist representation?James Hendler - 1990 - Behavioral and Brain Sciences 13 (3):496-497.
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  • Memories and functional response units.Kennon A. Lattal & Josele Abreu-Rodrigues - 1994 - Behavioral and Brain Sciences 17 (1):143-144.
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  • Comparison of Decision Learning Models Using the Generalization Criterion Method.Woo-Young Ahn, Jerome R. Busemeyer, Eric-Jan Wagenmakers & Julie C. Stout - 2008 - Cognitive Science 32 (8):1376-1402.
    It is a hallmark of a good model to make accurate a priori predictions to new conditions (Busemeyer & Wang, 2000). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the parameters for each participant from 1 task and using those same parameters to predict on the other task. Three methods were used to evaluate the (...)
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  • Sequential effects in response time reveal learning mechanisms and event representations.Matt Jones, Tim Curran, Michael C. Mozer & Matthew H. Wilder - 2013 - Psychological Review 120 (3):628-666.
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  • Are connectionist models just statistical pattern classifiers?Richard M. Golden - 1990 - Behavioral and Brain Sciences 13 (3):494-495.
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  • Crossword expertise as recognitional decision making: an artificial intelligence approach.Kejkaew Thanasuan & Shane T. Mueller - 2014 - Frontiers in Psychology 5.
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  • Expose hidden assumptions in network theory.Karl Haberlandt - 1990 - Behavioral and Brain Sciences 13 (3):495-496.
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  • Animal-centered models of reinforcement.William Timberlake - 1994 - Behavioral and Brain Sciences 17 (1):153-154.
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  • Killeen's theory provides an answer – and a question.Mary Ann Metzger & Terje Sagvolden - 1994 - Behavioral and Brain Sciences 17 (1):144-145.
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  • The return of the reinforcement theorists.C. D. L. Wynne - 1994 - Behavioral and Brain Sciences 17 (1):156-156.
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  • A mathematical theory of reinforcement: An unexpected place to find support for analogical memory coding.Donald M. Wilkie & Lisa M. Saksida - 1994 - Behavioral and Brain Sciences 17 (1):155-156.
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  • Fifty years on: The new “principles of behavior”?J. H. Wearden - 1994 - Behavioral and Brain Sciences 17 (1):155-155.
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  • Connectionist learning and the challenge of real environments.Mark Weaver & Stephen Kaplan - 1990 - Behavioral and Brain Sciences 13 (3):510-511.
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  • How general is a general theory of reinforcement?Stephen F. Walker - 1994 - Behavioral and Brain Sciences 17 (1):154-155.
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  • Smolensky's theory of mind.Paul F. M. J. Verschure - 1990 - Behavioral and Brain Sciences 13 (2):407-407.
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  • In defense of PTC.Paul Smolensky - 1990 - Behavioral and Brain Sciences 13 (2):407-412.
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  • Has learning been shown to be attractor modification within reinforcement modelling?Robert A. M. Gregson - 1994 - Behavioral and Brain Sciences 17 (1):140-141.
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  • Memory and the integration of response sequences.Phil Reed - 1994 - Behavioral and Brain Sciences 17 (1):148-149.
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  • Awareness and reinforcement.Charles P. Shimp - 1994 - Behavioral and Brain Sciences 17 (1):149-150.
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  • Evidence for Learning to Learn Behavior in Normal Form Games.Timothy C. Salmon - 2004 - Theory and Decision 56 (4):367-404.
    Evidence presented in Salmon (2001; Econometrica 69(6) 1597) indicates that typical tests to identify learning behavior in experiments involving normal form games possess little power to reject incorrect models. This paper begins by presenting results from an experiment designed to gather alternative data to overcome this problem. The results from these experiments indicate support for a learning-to-learn or rule learning hypothesis in which subjects change their decision rule over time. These results are then used to construct an adaptive learning model (...)
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  • Regularity Extraction Across Species: Associative Learning Mechanisms Shared by Human and Non‐Human Primates.Arnaud Rey, Laure Minier, Raphaëlle Malassis, Louisa Bogaerts & Joël Fagot - 2019 - Topics in Cognitive Science 11 (3):573-586.
    One of the themes that has been widely addressed in both the implicit learning and statistical learning literatures is that of rule learning. While it is widely agreed that the extraction of regularities from the environment is a fundamental facet of cognition, there is still debate about the nature of rule learning. Rey and colleagues show that the comparison between human and non‐human primates can contribute important insights to this debate.
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  • Level of analysis is not a central issue.James A. Reggia - 1990 - Behavioral and Brain Sciences 13 (2):406-407.
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  • The analysis of the learning needs to be deeper.John E. Rager - 1990 - Behavioral and Brain Sciences 13 (3):505-506.
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  • Effects of partial and continuous reinforcement on acquisition and extinction in classical appetitive conditioning.C. X. Poulos & I. Gormezano - 1974 - Bulletin of the Psychonomic Society 4 (3):197-198.
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  • Problems and pitfalls for Killeen's mathematical principles of reinforcement.Joseph J. Pear - 1994 - Behavioral and Brain Sciences 17 (1):146-147.
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  • Learning from learned networks.M. Pavel - 1990 - Behavioral and Brain Sciences 13 (3):503-504.
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  • Toward a unification of conditioning and cognition in animal learning.William S. Maki - 1990 - Behavioral and Brain Sciences 13 (3):501-502.
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  • Approaches to learning and representation.Pat Langley - 1990 - Behavioral and Brain Sciences 13 (3):500-501.
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  • Rats, responses and reinforcers: Using a little psychology on our subjects.Peter R. Killeen - 1994 - Behavioral and Brain Sciences 17 (1):157-172.
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  • The Temporal Context Model in Spatial Navigation and Relational Learning: Toward a Common Explanation of Medial Temporal Lobe Function Across Domains.Marc W. Howard, Mrigankka S. Fotedar, Aditya V. Datey & Michael E. Hasselmo - 2005 - Psychological Review 112 (1):75-116.
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  • Reinforcement without representation.Stephen José Hanson - 1994 - Behavioral and Brain Sciences 17 (1):141-142.
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  • Learning and representation: Tensions at the interface.Steven José Hanson - 1990 - Behavioral and Brain Sciences 13 (3):511-518.
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  • Smolensky's proper treatment of connectionism: Having it both ways.Vinod Goel - 1990 - Behavioral and Brain Sciences 13 (2):400-401.
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  • Sequential Dependencies in Driving.Anup Doshi, Cuong Tran, Matthew H. Wilder, Michael C. Mozer & Mohan M. Trivedi - 2012 - Cognitive Science 36 (5):948-963.
    The effect of recent experience on current behavior has been studied extensively in simple laboratory tasks. We explore the nature of sequential effects in the more naturalistic setting of automobile driving. Driving is a safety-critical task in which delayed response times may have severe consequences. Using a realistic driving simulator, we find significant sequential effects in pedal-press response times that depend on the history of recent stimuli and responses. Response times are slowed up to 100 ms in particular cases, a (...)
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  • The English past tense: Analogy redux.Steve Chandler - 2010 - Cognitive Linguistics 21 (3):371-417.
    The debate over how best to characterize inflectional morphology has been couched largely in terms of the “dual-mechanism” approach described in Pinker (Words and rules: the ingredients of language, Basic Books, 1999) versus “single-mechanism” connectionist approaches derived from Rumelhart and McClelland (On learning past tenses of English verbs, MIT, 1986). There are, however, other single-mechanism approaches. The exemplar-based or analogical models of Daelemans et al. (TimBL: Tilburg Memory-Based Learner, version 4.3 reference guide, ILK, 2002) and Skousen (Analogical modeling of language, (...)
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  • Linguistic problems in recent social research.Vladimir Cervin - 1956 - Synthese 10 (1):279 - 281.
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  • What connectionists learn: Comparisons of model and neural nets.Bruce Bridgeman - 1990 - Behavioral and Brain Sciences 13 (3):491-492.
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  • Validation of behavioural equations: Can neurobiology help?C. M. Bradshaw - 1994 - Behavioral and Brain Sciences 17 (1):136-137.
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  • Models of memory.Jeroen Gw Raaijmakers & Richard M. Shiffrin - 2002 - In J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology. Wiley.
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