Reasoning across continuous landscapes: A nonlinear dynamical systems theory approach to reasoning

Abstract

Dual-processing theories of reasoning have gained renewed attention in recent years, particularly in the fields of decision-making under uncertainty, learning, and social judgment. Although the various accounts differ, the common thread is the distinction between two qualitatively different reasoning processes, such as automatic/controlled, fast/slow, and unconscious/conscious. Accordingly, much research is focused on elucidating the nature of the two processes in terms of the kinds of information they process and respond to. Less extensive are attempts to identify mediators that underlie changes between the two reasoning strategies. We argue that nonlinear dynamical systems theory may be able to provide a fresh perspective on reasoning. Nonlinear dynamical systems theory allows us to shift the perspective to the dynamic interactions and transitions among continuous yet qualitatively different reasoning processes. We apply the approach to reasoning in decision-making and judgment under uncertainty. Our primary claim is that using different reasoning strategies is better understood as phase transitions among a landscape of continuous reasoning capacities.