A Survey on Interactive Reinforcement Learning
Christian Arzate Cruz, Takeo Igarashi
Abstract
Interactive reinforcement learning (RL) has been successfully used in various applications in different fields, which has also motivated HCI researchers to contribute in this area. In this paper, we survey interactive RL to empower human-computer interaction (HCI) researchers with the technical background in RL needed to design new interaction techniques and propose new applications. We elucidate the roles played by HCI researchers in interactive RL, identifying ideas and promising research directions. Furthermore, we propose generic design principles that will provide researchers with a guide to effectively implement interactive RL applications.
Topics & Concepts
Reinforcement learningComputer scienceHuman–computer interactionInteractive LearningInteraction designInteractive designMultimediaArtificial intelligenceReinforcement Learning in RoboticsEvolutionary Algorithms and ApplicationsMobile Crowdsensing and Crowdsourcing