Litcius/Paper detail

A Survey on Interactive Reinforcement Learning

Christian Arzate Cruz, Takeo Igarashi

202076 citationsDOI

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