In this review, we provide an overview of emerging trends and challenges in the field of
intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of …

Research into Explainable Artificial Intelligence (XAI) has been increasing in recent years as
a response to the need for increased transparency and trust in AI. This is particularly …

A prerequisite for social coordination is bidirectional communication between teammates,
each playing two roles simultaneously: as receptive listeners and expressive speakers. For …

Interpretability, explainability, and transparency are key issues to introducing artificial
intelligence methods in many critical domains. This is important due to ethical concerns and …

AI technologies have been incorporated into many end-user applications. However,
expectations of the capabilities of such systems vary among people. Furthermore, bloated …

Explainable AI (XAI) is widely viewed as a sine qua non for ever-expanding AI research. A
better understanding of the needs of XAI users, as well as human-centered evaluations of …

We propose an explainable reinforcement learning (XRL) framework that analyzes an
agent's history of interaction with the environment to extract interestingness elements that …

As robots become more and more capable and autonomous, there is an increasing need for
humans to understand what the robots do and think. In this paper, we investigate what such …

Abstract Purpose of Review As robots become increasingly prevalent and capable, the
complexity of roles and responsibilities assigned to them as well as our expectations for …

Advanced communication protocols are critical for the coexistence of autonomous robots
and humans. Thus, the development of explanatory capabilities in robots is an urgent first …