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  1. A Biologically Plausible Action Selection System for Cognitive Architectures: Implications of Basal Ganglia Anatomy for Learning and Decision‐Making Models.Andrea Stocco - 2018 - Cognitive Science 42 (2):457-490.
    Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of the basal ganglia—the existence of a direct and an indirect pathway that compete against each other. This characteristic has important consequences in decision-making tasks, which are brought to light by Parkinson's disease as (...)
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  • Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization.Fabian A. Soto, Samuel J. Gershman & Yael Niv - 2014 - Psychological Review 121 (3):526-558.
  • Perspectives on Modeling in Cognitive Science.Richard M. Shiffrin - 2010 - Topics in Cognitive Science 2 (4):736-750.
    This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author’s personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and for many, bewildering. Yet to come to anything approaching adequate insights into the infinitely complex fields of mind, brain, and intelligent (...)
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  • Models of visual word recognition.Dennis Norris - 2013 - Trends in Cognitive Sciences 17 (10):517-524.
  • Due Process in Dual Process: Model‐Recovery Simulations of Decision‐Bound Strategy Analysis in Category Learning.Charlotte E. R. Edmunds, Fraser Milton & Andy J. Wills - 2018 - Cognitive Science 42 (S3):833-860.
    Behavioral evidence for the COVIS dual‐process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, ). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to Decision Bound analysis (Maddox & Ashby, ). Here, we examine the accuracy of this analysis in a series of model‐recovery simulations. In Simulation 1, over a third of simulated participants using an (...)
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