activity
20152025
most citedHuman-level performance in first-person multiplayer games with population-based deep reinforcement learning

693 citations · 1.3k across the 11 of their papers we have counts for

collaborators
Showing cs.MAShow all

5 papers · 1 filter

cs.MA2025

Modeling human reputation-seeking behavior in a spatio-temporally complex public good provision game

Edward Hughes, Tina O. Zhu, Martin J. Chadwick +6

Multi-agent reinforcement learning algorithms are useful for simulating social behavior in settings that are too complex for other theoretical approaches like game theory. However,…

cs.MA2021★ 23 cited

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot

Joel Z. Leibo, Edgar Duéñez-Guzmán, Alexander Sasha Vezhnevets +7

Existing evaluation suites for multi-agent reinforcement learning (MARL) do not assess generalization to novel situations as their primary objective (unlike supervised-learning ben…

cs.MA2021★ 6 cited

A multi-agent reinforcement learning model of reputation and cooperation in human groups

Kevin R. McKee, Edward Hughes, Tina O. Zhu +7

Collective action demands that individuals efficiently coordinate how much, where, and when to cooperate. Laboratory experiments have extensively explored the first part of this pr…

cs.MA2021★ 18 cited

Quantifying the effects of environment and population diversity in multi-agent reinforcement learning

Kevin R. McKee, Joel Z. Leibo, Charlie Beattie +1

Generalization is a major challenge for multi-agent reinforcement learning. How well does an agent perform when placed in novel environments and in interactions with new co-players…

cs.MA2017★ 70 cited

A multi-agent reinforcement learning model of common-pool resource appropriation

Julien Perolat, Joel Z. Leibo, Vinicius Zambaldi +3

Humanity faces numerous problems of common-pool resource appropriation. This class of multi-agent social dilemma includes the problems of ensuring sustainable use of fresh water, c…