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  1. Classical Computational Models.Richard Samuels - 2018 - In Mark Sprevak & Matteo Colombo (ed.), The Routledge Handbook of the Computational Mind. Oxford, UK: pp. 103-119.
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  • Dividing Attention Between Tasks: Testing Whether Explicit Payoff Functions Elicit Optimal Dual-Task Performance.George D. Farmer, Christian P. Janssen, Anh T. Nguyen & Duncan P. Brumby - 2018 - Cognitive Science 42 (3):820-849.
    We test people's ability to optimize performance across two concurrent tasks. Participants performed a number entry task while controlling a randomly moving cursor with a joystick. Participants received explicit feedback on their performance on these tasks in the form of a single combined score. This payoff function was varied between conditions to change the value of one task relative to the other. We found that participants adapted their strategy for interleaving the two tasks, by varying how long they spent on (...)
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  • Sculpting Computationalā€Level Models.Mark Blokpoel - 2018 - Topics in Cognitive Science 10 (3):641-648.
    In this commentary, I advocate for strict relations between Marr's levels of analysis. Under a strict relationship, each level is exactly implemented by the subordinate level. This yields two benefits. First, it brings consistency for multilevel explanations. Second, similar to how a sculptor chisels away superfluous marble, a modeler can chisel a computational-level model by applying constraints. By sculpting the model, one restricts the set of possible algorithmic- and implementational-level theories.
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