Autonomous development of turn-taking behaviors in agent populations: a computational study

Abstract

We provide an original computational model showing how turn-taking behaviors can self-organize out of sensorimotor/ninteractions between vocalizing agents. These agents are equipped with a cognitive architecture based on two coupled/ncontrol loops: a reactive one implementing a basic regulatory behavior to maintain vocal listening and an adaptive one learning an action policy to maximize an overall group presence estimation. We show that the reactive process allows to bootstrap the adaptive learning to converge toward a collective turn-taking strategy. This model provides a computational support to the hypothesis that turn-taking can emerge from functional constraints related to group cohesion and vocal signal interferences and suggests future directions of research to understand how social behaviors/ncan result from sensorimotor interactions.