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 …

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 …

The recent years have witnessed a dramatic increase in the use of reinforcement learning
(RL) models in social, cognitive and affective neuroscience. This approach, in combination …

Individuals exhibit theory of mind, attributing beliefs, intent, and mental states to others as
explanations of observed actions. Dennett's intentional stance offers an analogous …

This paper considers the challenging tasks of Multi-Agent Reinforcement Learning (MARL)
under partial observability, where each agent only sees her own individual observations and …

Causal reasoning and game-theoretic reasoning are fundamental topics in artificial
intelligence, among many other disciplines: this paper is concerned with their intersection …

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 …

This paper presents a theoretical advance by which factored POSGs can be decomposed
into local models. We formalize the interface between such local models as the influence …

This article presents the state-of-the-art in optimal solution methods for decentralized
partially observable Markov decision processes (Dec-POMDPs), which are general models …

Although multi-robot systems have received substantial re-search attention in recent years,
multi-robot coordination still remains a difficult task. Especially, when dealing with spatially …