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  1. Deconstructing the human algorithms for exploration.Samuel J. Gershman - 2018 - Cognition 173 (C):34-42.
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  • A theory of attention: Variations in the associability of stimuli with reinforcement.N. J. Mackintosh - 1975 - Psychological Review 82 (4):276-298.
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  • Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic.Thomas L. Griffiths, Falk Lieder & Noah D. Goodman - 2015 - Topics in Cognitive Science 7 (2):217-229.
    Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the (...)
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  • A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli.John M. Pearce & Geoffrey Hall - 1980 - Psychological Review 87 (6):532-552.
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  • Principles of metareasoning.Stuart Russell & Eric Wefald - 1991 - Artificial Intelligence 49 (1-3):361-395.
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  • The primacy model: A new model of immediate serial recall.Michael P. A. Page & Dennis Norris - 1998 - Psychological Review 105 (4):761-781.
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  • Working memory, short-term memory, and general fluid intelligence: a latent-variable approach.Randall W. Engle, Stephen W. Tuholski, James E. Laughlin & Andrew R. A. Conway - 1999 - Journal of Experimental Psychology: General 128 (3):309.
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