Study reproducibility and generalizability of results to broadly inclusive populations is crucial
in any research. Previous meta-analyses in HRI have focused on the consistency of reported …

The field of AI Ethics has recently gained considerable attention, yet much of the existing
academic research lacks practical and objective contributions for the development of ethical …

In recent years, the affective computing (AC) and human-robot interaction (HRI) research
communities have put fairness at the centre of their research agenda. However, none of the …

This paper proposes SCALES, a general framework that translates well-established fairness
principles into a common representation based on the Constraint Markov Decision Process …

Intelligent robots designed for real-world human interactions need to adapt to the diverse
preferences of individuals. Preference-based Reinforcement Learning (PbRL) offers …

Research has shown that data-driven robots deployed in social settings are likely to
unconsciously perpetuate systemic social biases. Despite this, robots can also be deployed …

This study aimed to explore the implementation of fairness in intelligent agents to enhance
their interactions in our social space. Two distinct investigations, an experiment, and a focus …

Robots are already entering our homes and workplaces, and they are increasingly put in the
role of a teammate working with teams of humans. Designing effective robotic teammates is …

Robot learning from humans has been proposed and researched for several decades as a
means to enable robots to learn new skills or adapt existing ones to new situations. Recent …