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  1. Absolute Identification by Relative Judgment.Neil Stewart, Gordon D. A. Brown & Nick Chater - 2005 - Psychological Review 112 (4):881-911.
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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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  • Practical effects of response specification.Richard L. Shull - 1994 - Behavioral and Brain Sciences 17 (1):150-150.
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  • Awareness and reinforcement.Charles P. Shimp - 1994 - Behavioral and Brain Sciences 17 (1):149-150.
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  • There is more to learning then meeth the eye.Noel E. Sharkey - 1990 - Behavioral and Brain Sciences 13 (3):506-507.
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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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  • How persuasive is a good fit? A comment on theory testing.Seth Roberts & Harold Pashler - 2000 - Psychological Review 107 (2):358-367.
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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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  • From overt behavior to hypothetical behavior to memory: Inference in the wrong direction.Howard Rachlin - 1994 - Behavioral and Brain Sciences 17 (1):147-148.
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  • Information processing and the decremental effect of intermittent reinforcement schedules in human conditioning.William F. Prokasy & William C. Williams - 1979 - Bulletin of the Psychonomic Society 14 (1):57-60.
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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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  • Realistic neural nets need to learn iconic representations.W. A. Phillips, P. J. B. Hancock & L. S. Smith - 1990 - Behavioral and Brain Sciences 13 (3):505-505.
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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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  • Connectionism: Self-abuse is improper treatment.Gregg C. Oden - 1990 - Behavioral and Brain Sciences 13 (2):402-402.
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  • Keeping representations at bay.Stanley Munsat - 1990 - Behavioral and Brain Sciences 13 (3):502-503.
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  • Evolution and connectionism.Neil McNaughton - 1990 - Behavioral and Brain Sciences 13 (2):402-403.
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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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  • 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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  • Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation.Kevin Lloyd, Adam Sanborn, David Leslie & Stephan Lewandowsky - 2019 - Cognitive Science 43 (12):e12805.
    Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the number of samples, or “particles,” available to perform inference. To test this idea, we focus on two recent experiments that report positive associations between WMC and two distinct (...)
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  • Approaches to learning and representation.Pat Langley - 1990 - Behavioral and Brain Sciences 13 (3):500-501.
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  • How connectionist models learn: The course of learning in connectionist networks.John K. Kruschke - 1990 - Behavioral and Brain Sciences 13 (3):498-499.
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  • Integration and specificity of retrieval in a memory-based model of reinforcement.Marvin D. Krank - 1994 - Behavioral and Brain Sciences 17 (1):142-143.
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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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  • Mathematical principles of reinforcement.Peter R. Killeen - 1994 - Behavioral and Brain Sciences 17 (1):105-135.
    Effective conditioning requires a correlation between the experimenter's definition of a response and an organism's, but an animal's perception of its behavior differs from ours. These experiments explore various definitions of the response, using the slopes of learning curves to infer which comes closest to the organism's definition. The resulting exponentially weighted moving average provides a model of memory that is used to ground a quantitative theory of reinforcement. The theory assumes that: incentives excite behavior and focus the excitement on (...)
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  • A non-empiricist perspective on learning in layered networks.Michael I. Jordan - 1990 - Behavioral and Brain Sciences 13 (3):497-498.
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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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  • Moving beyond schedules and rate: A new trajectory?Gregory Galbicka - 1994 - Behavioral and Brain Sciences 17 (1):139-140.
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  • The role of cognitive abilities in decisions from experience: Age differences emerge as a function of choice set size.Renato Frey, Rui Mata & Ralph Hertwig - 2015 - Cognition 142 (C):60-80.
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  • On Adaptation, Maximization, and Reinforcement Learning Among Cognitive Strategies.Ido Erev & Greg Barron - 2005 - Psychological Review 112 (4):912-931.
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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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  • 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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  • A property cluster theory of cognition.Cameron Buckner - 2015 - Philosophical Psychology 28 (3):307-336.
    Our prominent definitions of cognition are too vague and lack empirical grounding. They have not kept up with recent developments, and cannot bear the weight placed on them across many different debates. I here articulate and defend a more adequate theory. On this theory, behaviors under the control of cognition tend to display a cluster of characteristic properties, a cluster which tends to be absent from behaviors produced by non-cognitive processes. This cluster is reverse-engineered from the empirical tests that comparative (...)
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  • Representational systems and symbolic systems.Gordon D. A. Brown & Mike Oaksford - 1990 - Behavioral and Brain Sciences 13 (3):492-493.
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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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  • The response problem.Robert C. Bolles - 1994 - Behavioral and Brain Sciences 17 (1):135-136.
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  • Naturalistic multiattribute choice.Sudeep Bhatia & Neil Stewart - 2018 - Cognition 179 (C):71-88.
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  • Relatively local neurons in a distributed representation: A neurophysiological perspective.Shabtai Barash - 1990 - Behavioral and Brain Sciences 13 (3):489-491.
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  • The use of models in experimental psychology.Richard C. Atkinson - 1960 - Synthese 12 (2-3):162 - 171.
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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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