From Cognitive Agents to Cognitive Systems: Theoretical, Methodological, and Empirical Developments of van Gelder's (1998) “Dynamical Hypothesis”

Author:

Nguyen Tri D.1,Magaldino Corey M.1,Landfair Jayci T.1,Amazeen Polemnia G.1,Amazeen Eric L.1

Affiliation:

1. Department of Psychology Arizona State University

Abstract

AbstractOver two decades have passed since the publication of van Gelder's (1998) “dynamical hypothesis.” In that paper, van Gelder proposed that cognitive agents were not digital computers—per the representational computational approach—but dynamical systems. The evolution of the dynamical hypothesis was driven by parallel advances in three areas. Theoretically, a deeper understanding of genetics, biology, neuroscience, and cognitive science inspired questions about how systems within each domain dynamically interact and extend their effects across spatiotemporal scales. Methodologically, more sophisticated and domain‐general tools allowed researchers to discover, model, and quantify system dynamics, structure, and patterns across multiple scales to generate a more comprehensive system‐level understanding of behaviors. Empirically, we can analyze a system's behavior while preserving its natural dynamics, revealing evidence that the reductionist approach leads to an incomplete understanding of the components and the overall system. Researchers have traditionally reduced a complex system into its component processes and assumed that the parts can be recombined to explain the whole. These three advances fundamentally altered our understanding of a “cognitive agent:” How their behaviors are driven by long‐range coordination across multiple processes, how the interdependent and nested structure of interacting variables produces behaviors that are greater than the sum of its parts, and how environmental constraints shape adaptive yet stable behavioral patterns.

Funder

Army Research Laboratory

Publisher

Wiley

Reference107 articles.

1. Abraham R. H. &Shaw C. D.(1992).Dynamics: The geometry of behavior.Redwood City CA:Addison‐Wesley.

2. Allen L. K. Likens A. D. &McNamara D. S.(2017).Recurrence quantification analysis: A technique for the dynamical analysis of student writing. InProceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference(pp.240–245).Palo Alto CA:AAAI Press.

3. From physics to social interactions: Scientific unification via dynamics;Amazeen P. G.;Cognitive Systems Research,2018

4. Recurrence quantification analysis of eye movements;Anderson N. C.;Behavior Research Methods,2013

5. Systems pharmacology of arrhythmias;Berger S. I.;Science Signaling,2010

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3