Abstract

This paper explores some of the insights offered by a dynamic systems approach into the nature of habits. “Dynamic systems approach” is used here as an umbrella term for studies of cognition, behavior, or development as systems of elements that change over time (e.g., Thelen and Smith, 1994, 2006), while “dynamical systems” is reserved for studies that use differential equations to describe time-based systems (e.g., Schoner and Kelso, 1988; Tschacher and Dauwalder, 2003). The following discussion draws primarily from the coordination dynamics research of Kelso (1995, 2012), which stems from Haken's theory of synergetics (1977, 2003). However, the view of habits presented here is more of an interpretive application than a literature review, as the work on which it draws does not address habits explicitly. Perhaps this is because conventional notions of habit are too broad and loose to be captured succinctly in dynamic terms. Dynamical studies of human behavior have focused on more specific capacities such as motor coordination (Thelen et al., 1987), perception (Tuller et al., 1994), and learning (Kostrubiec et al., 2012). Yet this variety of applications suggests that the scope of the dynamic approach overlaps significantly with the domain of habits, so that dynamic concepts could be used to challenge and refine our conventional notions of habitual behavior. Accordingly, the goal of this paper is to raise questions about the nature of habits rather than present a comprehensive scientific theory.

Highlights

  • Edited by: Jose Angel Lombo, Pontifical University of the Holy Cross, Italy Reviewed by: Scott Kelso, Florida Atlantic University, USA

  • This paper explores some of the insights offered by a dynamic systems approach into the nature of habits

  • The following discussion explores the implications of four features of dynamic system stability for our understanding of habit: (1) stability is relative to timescale, and system stabilities at different timescales are interdependent; (2) the attractor landscape describing the characteristic stabilities of a system can be altered by various control parameters, including situational parameters; (3) systems can have multiple stabilities, such that the stability they exhibit at any given time may depend on their recent history; (4) learning processes tend to affect a whole cluster of interrelated stabilities and not just one stability in isolation

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Summary

Introduction

Edited by: Jose Angel Lombo, Pontifical University of the Holy Cross, Italy Reviewed by: Scott Kelso, Florida Atlantic University, USA. The following discussion explores the implications of four features of dynamic system stability for our understanding of habit: (1) stability is relative to timescale, and system stabilities at different timescales are interdependent; (2) the attractor landscape describing the characteristic stabilities of a system can be altered by various control parameters, including situational parameters; (3) systems can have multiple stabilities, such that the stability they exhibit at any given time may depend on their recent history; (4) learning processes tend to affect a whole cluster of interrelated stabilities and not just one stability in isolation.

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