Mechanisms for Robust Cognition. (29th October 2014)

• Record Type: Journal Article
• Authors: Walsh, Matthew M.; Gluck, Kevin A.
• Is Part Of: Cognitive science. Volume 39:Number 6(2015:Aug.)
• Page Start: 1131
• Page End: 1171
• Publication Date: 2014-10-29
• Subjects: Cognition -- Periodicals; Psycholinguistics -- Periodicals; Artificial intelligence -- Periodicals; 153.05
• DOI: 10.1111/cogs.12192
• Languages: English
• ISSNs: 0364-0213

Abstract

<abstract abstract-type="main" id="cogs12192-abs-0001"> <title>Abstract</title> <p>To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within variable environments. This raises the question, how do cognitive systems achieve similarly high degrees of robustness? The aim of this study was to identify a set of mechanisms that enhance robustness in cognitive systems. We identify three mechanisms that enhance robustness in biological and engineered systems: <italic>system control</italic>, <italic> redundancy</italic>, and <italic>adaptability</italic>. After surveying the psychological literature for evidence of these mechanisms, we provide simulations illustrating how each contributes to robust cognition in a different psychological domain: psychomotor vigilance, semantic memory, and strategy selection. These simulations highlight features of a mathematical approach for quantifying robustness, and they provide concrete examples of mechanisms for robust cognition.</p> </abstract>