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 …

The increasing penetration of renewable generations, along with the deregulation and
marketization of power industry, promotes the transformation of energy market operation …

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 …

Opponent modeling is the ability to use prior knowledge and observations in order to predict
the behavior of an opponent. This survey presents a comprehensive overview of existing …

This paper describes a novel method for building affectively intelligent human-interactive
agents. The method is based on a key sociological insight that has been developed and …

People often give instructions whose meaning is ambiguous without further context,
expecting that their actions or goals will disambiguate their intentions. How can we build …

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 …

In open multiagent systems, the set of agents operating in the environment changes over
time and in ways that are nontrivial to predict. For example, if collaborative robots were …