The Importance of Falsification in Computational Cognitive Modeling.

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Ten simple rules for the computational modeling of behavioral data (2019, methodology): “Palminteri and colleagues (Palminteri et al., 2017) offer a striking example of this effect, where Model A fits better than Model B by any quantitative measure of model comparison, but is completely unable to capture the essence of the behavior.”