Learning from humans to build social cognition among robots

Frontiers in Robotics and AI

Robotics and AI

Axel Cleeremans¹  Mary Katherine Heinrich²  Marco Dorigo²  Nicolas Coucke³ 

[1] Consciousness, Cognition and Computation Group, Center for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium;IRIDIA, Université Libre de Bruxelles, Brussels, Belgium;IRIDIA, Université Libre de Bruxelles, Brussels, Belgium;Consciousness, Cognition and Computation Group, Center for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium;

关键词: artificial social cognition;    embodied cognition;    self-organization;    robot swarms;    multi-robot systems;    artificial intelligence;    artificial general intelligence;    social robots;   

DOI  :  10.3389/frobt.2023.1030416

 received in 2022-08-28, accepted in 2023-01-23,  发布年份 2023

来源: Frontiers

【 摘 要 】

Self-organized groups of robots have generally coordinated their behaviors using quite simple social interactions. Although simple interactions are sufficient for some group behaviors, future research needs to investigate more elaborate forms of coordination, such as social cognition, to progress towards real deployments. In this perspective, we define social cognition among robots as the combination of social inference, social learning, social influence, and knowledge transfer, and propose that these abilities can be established in robots by building underlying mechanisms based on behaviors observed in humans. We review key social processes observed in humans that could inspire valuable capabilities in robots and propose that relevant insights from human social cognition can be obtained by studying human-controlled avatars in virtual environments that have the correct balance of embodiment and constraints. Such environments need to allow participants to engage in embodied social behaviors, for instance through situatedness and bodily involvement, but, at the same time, need to artificially constrain humans to the operational conditions of robots, for instance in terms of perception and communication. We illustrate our proposed experimental method with example setups in a multi-user virtual environment.

【 授权许可】

Unknown   
Copyright © 2023 Coucke, Heinrich, Cleeremans and Dorigo.