# Can User-Centered Reinforcement Learning Allow a Robot to Attract Passersby without Causing Discomfort?

## TL;DR

This study introduces a user-centered reinforcement learning approach enabling social robots to greet passersby effectively without causing discomfort, demonstrated through field experiments at an office entrance.

## Contribution

The paper presents a novel reinforcement learning method tailored for social robots to adapt their greetings based on passersby reactions, reducing discomfort.

## Key findings

- Robots using the method successfully avoided causing discomfort (p<0.01).
- Field experiments confirmed the effectiveness of the approach in real-world settings.
- The approach improved passersby's comfort and attention engagement.

## Abstract

The aim of our study was to develop a method by which a social robot can greet passersby and get their attention without causing them to suffer discomfort.A number of customer services have recently come to be provided by social robots rather than people, including, serving as receptionists, guides, and exhibitors. Robot exhibitors, for example, can explain products being promoted by the robot owners. However, a sudden greeting by a robot can startle passersby and cause discomfort to passersby.Social robots should thus adapt their mannerisms to the situation they face regarding passersby.We developed a method for meeting this requirement on the basis of the results of related work. Our proposed method, user-centered reinforcement learning, enables robots to greet passersby and get their attention without causing them to suffer discomfort (p<0.01) .The results of an experiment in the field, an office entrance, demonstrated that our method meets this requirement.