Nash equilibria in human sensorimotor interactions explained by Q-learning with intrinsic costs.

ABSTRACT: The Nash equilibrium concept has previously been shown to be an important tool to understand human sensorimotor interactions, where different actors vie for minimizing their respective effort while engaging in a multi-agent motor task. However, it is not clear how such equilibria are reached. Here, we compare different reinforcement learning models to human behavior engaged in sensorimotor interactions with haptic feedback based on three classic games, including the prisoner's dilemma, and the symmetric and asymmetric matching pennies games. We find that a discrete analysis that reduces the continuous sensorimotor interaction to binary choices as in classical matrix games does not allow to distinguish between the different learning algorithms, but that a more detailed continuous analysis w

SUBMITTER: Lindig-Leon C 

PROVIDER: S-EPMC8531365 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature