Abstract Concepts Require Concrete Models: Why Cognitive Scientists Have Not Yet Embraced Nonlinearly Coupled, Dynamical, Self-Organized Critical, Synergistic, Scale-Free, Exquisitely Context-Sensitive, Interaction-Dominant, Multifractal, Interdependent Brain-Body-Niche Systems
Topics in Cognitive Science 4 (1):87-93 (2012)
Abstract
After more than 15 years of study, the 1/f noise or complex-systems approach to cognitive science has delivered promises of progress, colorful verbiage, and statistical analyses of phenomena whose relevance for cognition remains unclear. What the complex-systems approach has arguably failed to deliver are concrete insights about how people perceive, think, decide, and act. Without formal models that implement the proposed abstract concepts, the complex-systems approach to cognitive science runs the danger of becoming a philosophical exercise in futility. The complex-systems approach can be informative and innovative, but only if it is implemented as a formal model that allows concrete prediction, falsification, and comparison against more traditional approachesDOI
10.1111/j.1756-8765.2011.01164.x
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Citations of this work
A comparison of information processing and dynamical systems perspectives on problem solving.Stephen K. Reed & Robin R. Vallacher - 2019 - Thinking and Reasoning 26 (2):254-290.
Is Cognitive Science Usefully Cast as Complexity Science?Guy Van Orden & Damian G. Stephen - 2012 - Topics in Cognitive Science 4 (1):3-6.
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Behavior Stability and Individual Differences in Pavlovian Extended Conditioning.Gianluca Calcagni, Ernesto Caballero-Garrido & Ricardo Pellón - 2020 - Frontiers in Psychology 11.
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