Much research in artificial intelligence is concerned with the development of autonomous
agents that can interact effectively with other agents. An important aspect of such agents is …

Intelligent transport systems, efficient electric grids, and sensor networks for data collection
and analysis are some examples of the multiagent systems (MAS) that cooperate to achieve …

Humans are capable of attributing latent mental contents such as beliefs or intentions to
others. The social skill is critical in daily life for reasoning about the potential consequences …

Researchers have observed that people will more accurately trust an autonomous system,
such as a robot, if they have a more accurate understanding of its decision-making process …

There is a long history in game theory on the topic of Bayesian or “rational” learning, in
which each player maintains beliefs over a set of alternative behaviours, or types, for the …

While machines and robots must interact with humans, providing them with social skills has
been a largely overlooked topic. This is mostly a consequence of the fact that tasks such as …

Partially observable Markov decision processes (POMDPs) provide a principled framework
for sequential planning in uncertain single agent settings. An extension of POMDPs to …

Being aware of observers and the inferences they make about an agent's behavior is crucial
for successful multi-agent interaction. Existing works on observer-aware planning use …

A key challenge in non-cooperative multi-agent systems is that of developing efficient
planning algorithms for intelligent agents to interact and perform effectively among …

Technological advances offer the promise of robotic systems that work with people to form
human-robot teams that are more capable than their individual members. Unfortunately, the …