This paper investigates the use of model-based reinforcement learning in the context of ad
hoc teamwork. We introduce a novel approach, named TEAMSTER, where we propose …

Many scenarios require that robots work together as a team in order to effectively
accomplish their tasks. However, pre-coordinating these teams may not always be possible …

Robust autonomous agents should be able to cooperate with new teammates effectively by
employing ad hoc teamwork. Reasoning about ad hoc teamwork allows agents to perform …

Ad hoc teamwork problem describes situations where an agent has to cooperate with
previously unseen agents to achieve a common goal. For an agent to be successful in these …

Ad hoc teamwork is the challenging problem of designing an autonomous agent which can
adapt quickly to collaborate with teammates without prior coordination mechanisms …

When performing collaborative tasks with new unknown teammates, humans are particularly
adept at adapting to their collaborator and converging toward an aligned strategy. However …

In this paper we address the problem of ad hoc teamwork and contribute a novel approach,
PPAS, that is able to handle non-stationary teammates. Current approaches to ad hoc …

Open ad hoc teamwork is the problem of training a single agent to efficiently collaborate with
an unknown group of teammates whose composition may change over time. A variable team …

Training agents in cooperative settings offers the promise of AI agents able to interact
effectively with humans (and other agents) in the real world. Multi-agent reinforcement …

While great strides have been made in multiagent teamwork, existing approaches typically
assume extensive information exists about teammates and how to coordinate actions. This …