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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 collaboration with unknown teammates performing an unknown task without needing a pre-coordination protocol.
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On the utility of learning about humans for human-AI coordination. In Adv. Neural Information Processing Systems 32
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“Other-Play” for Zero-Shot Coordination. In International Conference on Machine Learning . PMLR, 4399–4410
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Quasi-Equivalence Discovery for Zero-Shot Emergent Communication
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Trajectory diversity for zero-shot coordination. In International Conference on Machine Learning . PMLR, 7204–7213
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Ad hoc teamwork by learning teammates’ task
F. Melo and A. Sardinha. 2016 · 2016
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Making friends on the fly: Cooperating with new teammates
S. Barrett, A. Rosenfeld, S. Kraus, and P. Stone. 2017 · 2017
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Ad hoc autonomous agent teams: Collaboration without pre-coordination. In Proc. 24th AAAI Conf. Artificial Intelligence . 1504–1509
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Leading a best-response teammate in an ad hoc team
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Helping People on the Fly: Ad Hoc Teamwork for Human-Robot Teams. In EPIA Conference on Artificial Intelligence . Springer, 635–647
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A New Formalism, Method and Open Issues for Zero-Shot Coordination
Johannes Treutlein, Michael Dennis, Caspar Oesterheld, and Jakob Foerster. 2021 · 2021
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