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  1. Modeling How, When, and What Is Learned in a Simple Fault‐Finding Task.Frank E. Ritter & Peter A. Bibby - 2008 - Cognitive Science 32 (5):862-892.
    We have developed a process model that learns in multiple ways while finding faults in a simple control panel device. The model predicts human participants' learning through its own learning. The model's performance was systematically compared to human learning data, including the time course and specific sequence of learned behaviors. These comparisons show that the model accounts very well for measures such as problem‐solving strategy, the relative difficulty of faults, and average fault‐finding time. More important, because the model learns and (...)
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  • Scrutinizing visual images: The role of gaze in mental imagery and memory.Bruno Laeng, Ilona M. Bloem, Stefania D’Ascenzo & Luca Tommasi - 2014 - Cognition 131 (2):263-283.
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  • Memory for goals: an activation‐based model.Erik M. Altmann & J. Gregory Trafton - 2002 - Cognitive Science 26 (1):39-83.
    Goal‐directed cognition is often discussed in terms of specialized memory structures like the “goal stack.” The goal‐activation model presented here analyzes goal‐directed cognition in terms of the general memory constructs of activation and associative priming. The model embodies three predictive constraints: (1) the interference level, which arises from residual memory for old goals; (1) the strengthening constraint, which makes predictions about time to encode a new goal; and (3) the priming constraint, which makes predictions about the role of cues in (...)
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