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  1. (1 other version)Finding Structure in Time.Jeffrey L. Elman - 1990 - Cognitive Science 14 (2):179-211.
    Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...)
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  • Doing Without Schema Hierarchies: A Recurrent Connectionist Approach to Normal and Impaired Routine Sequential Action.Matthew Botvinick & David C. Plaut - 2004 - Psychological Review 111 (2):395-429.
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  • Are theories of learning necessary?B. F. Skinner - 1950 - Psychological Review 57 (4):193-216.
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  • The theory of event coding (TEC): A framework for perception and action planning.Bernhard Hommel, Jochen Müsseler, Gisa Aschersleben & Wolfgang Prinz - 2001 - Behavioral and Brain Sciences 24 (5):849-878.
    Traditional approaches to human information processing tend to deal with perception and action planning in isolation, so that an adequate account of the perception-action interface is still missing. On the perceptual side, the dominant cognitive view largely underestimates, and thus fails to account for, the impact of action-related processes on both the processing of perceptual information and on perceptual learning. On the action side, most approaches conceive of action planning as a mere continuation of stimulus processing, thus failing to account (...)
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  • Short Term Gains, Long Term Pains: How Cues About State Aid Learning in Dynamic Environments.Bradley C. Love Todd M. Gureckis - 2009 - Cognition 113 (3):293.
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  • The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity.Clay B. Holroyd & Michael G. H. Coles - 2002 - Psychological Review 109 (4):679-709.
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  • Implicit sequence learning and conscious awareness.Qiufang Fu, Xiaolan Fu & Zoltán Dienes - 2008 - Consciousness and Cognition 17 (1):185-202.
    This paper uses the Process Dissociation Procedure to explore whether people can acquire unconscious knowledge in the serial reaction time task [Destrebecqz, A., & Cleeremans, A. . Can sequence learning be implicit? New evidence with the Process Dissociation Procedure. Psychonomic Bulletin & Review, 8, 343–350; Wilkinson, L., & Shanks, D. R. . Intentional control and implicit sequence learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 354–369]. Experiment 1 showed that people generated legal sequences above baseline levels under exclusion (...)
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  • Short-term gains, long-term pains: How cues about state aid learning in dynamic environments.Todd M. Gureckis & Bradley C. Love - 2009 - Cognition 113 (3):293-313.
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  • MDLChunker: A MDL-Based Cognitive Model of Inductive Learning.Vivien Robinet, Benoît Lemaire & Mirta B. Gordon - 2011 - Cognitive Science 35 (7):1352-1389.
    This paper presents a computational model of the way humans inductively identify and aggregate concepts from the low-level stimuli they are exposed to. Based on the idea that humans tend to select the simplest structures, it implements a dynamic hierarchical chunking mechanism in which the decision whether to create a new chunk is based on an information-theoretic criterion, the Minimum Description Length (MDL) principle. We present theoretical justifications for this approach together with results of an experiment in which participants, exposed (...)
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  • TRACX: A recognition-based connectionist framework for sequence segmentation and chunk extraction.Robert M. French, Caspar Addyman & Denis Mareschal - 2011 - Psychological Review 118 (4):614-636.
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