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 …

In this paper, we present a novel Bayesian online prediction algorithm for the problem
setting of ad hoc teamwork under partial observability (ATPO), which enables on-the-fly …

This paper introduces a formal definition of the setting of ad hoc teamwork under partial
observability and proposes a first-principled model-based approach which relies only on …

Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the “ad hoc
agent”) must successfully collaborate with a set of unknown agents (the “teammates”) …

A key goal of ad hoc teamwork is to develop a learning agent that cooperates with unknown
teams, without resorting to any pre-coordination protocol. Despite a vast number of ad hoc …

Ad Hoc Teamwork environments are dynamic spaces where agents engage in activities,
make decisions, and collaborate with teammates without prior coordination or complete …

Ad hoc teamwork addresses the challenge of collaborating with unknown agents without
prior coordination methods. When addressing the ad hoc teamwork problem between …