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Multi-scale resolution of neural, cognitive and social systems

Mark G. Orr (), Christian Lebiere, Andrea Stocco, Peter Pirolli, Bianica Pires and William G. Kennedy
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Mark G. Orr: University of Virginia
Christian Lebiere: Carnegie Mellon University
Andrea Stocco: University of Washington
Peter Pirolli: Institute for Human and Machine Cognition
Bianica Pires: Virginia Tech
William G. Kennedy: George Mason University

Computational and Mathematical Organization Theory, 2019, vol. 25, issue 1, No 2, 4-23

Abstract: Abstract We recently put forth a thesis, the Resolution Thesis, that suggests that cognitive science and generative social science are interdependent and should thus be mutually informative. The thesis invokes a paradigm, the reciprocal constraints paradigm, that was designed to leverage the interdependence between the social and cognitive levels of scale for the purpose of building cognitive and social simulations with better resolution. We review our thesis here, provide the current research context, address a set of issues with the thesis, and provide some parting thoughts to provoke discussion. We see this work as an initial step to motivate both social and cognitive sciences in a new direction, one that represents unity of purpose, an interdependence of theory and methods, and a call for the careful development of new approaches for understanding human social systems, broadly construed.

Keywords: Cognitive modeling; Agent-based modeling; Social simulation; Multi-scale systems (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10588-018-09291-0

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