Predictive joint-action model: A hierarchical predictive approach to human cooperation.

Abstract

Research in a number of related fields has recently begun to focus on the perceptual, cognitive, and motor workings of cooperative behavior. There appears to be enough coherence in these efforts to refer to the study of the mechanisms underlying human cooperative behavior as the field of joint-action (Knoblich, Butterfill, & Sebanz, 2011; Sebanz, Bekkering, & Knoblich, 2006). Yet, the development of theory in this field has not kept pace with the proliferation of research findings. We propose a hierarchical predictive framework for the study of joint-action that we call the predictive joint-action model (PJAM). The presentation of this theoretical framework is organized into three sections. In the first section, we summarize hierarchical predictive principles and discuss their application to joint-action. In the second section, we juxtapose PJAM's assumptions with empirical evidence from the current literature on joint-action. In the third section, we discuss the overall success of the hierarchical predictive approach to account for the burgeoning empirical literature on joint-action research. Finally, we consider the model's capacity to generate novel and testable hypotheses about joint-action. This is done with the larger goal of uncovering the empirical and theoretical pieces that are still missing in a comprehensive understanding of joint action.