This article presents a survey of literature in the area of Human–Robot Interaction (HRI),
specifically on systems containing more than two agents (ie, having multiple humans and/or …

Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …

When robots interact with humans in homes, roads, or factories the human's behavior often
changes in response to the robot. Non-stationary humans are challenging for robot learners …

When robots interact with human partners, often these partners change their behavior in
response to the robot. On the one hand this is challenging because the robot must learn to …

Recent works explore collaboration between humans and teams of robots. These
approaches make sense if the human is already working with the robot team; but how …

When humans interact with robots influence is inevitable. Consider an autonomous car
driving near a human: the speed and steering of the autonomous car will affect how the …

Humans routinely form groups to achieve goals that no individual can accomplish alone.
Group coordination often brings to mind synchrony and alignment, where all individuals do …

This paper introduces an innovative approach to addressing leader-follower control
challenges through iterative learning techniques. In this scheme, both the leader and the …

The likelihood of an agent's success in achieving its goals and subgoals under specific
operational constraints is an important factor in performance-based trust. Trust management …

The growing presence of modern learning robots necessitates a fundamental shift in design,
as these robots must learn skills from human inputs. Two main components close the loop in …