1.1k citations · 1.6k across the 11 of their papers we have counts for
4 papers · 1 filter
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments
Ian Gemp, Thomas Anthony, Yoram Bachrach +24
The Game Theory & Multi-Agent team at DeepMind studies several aspects of multi-agent learning ranging from computing approximations to fundamental concepts in game theory to simul…
A Generalized Training Approach for Multiagent Learning
Paul Muller, Shayegan Omidshafiei, Mark Rowland +12
This paper investigates a population-based training regime based on game-theoretic principles called Policy-Spaced Response Oracles (PSRO). PSRO is general in the sense that it (1)…
-Rank: Multi-Agent Evaluation by Evolution
Shayegan Omidshafiei, Christos Papadimitriou, Georgios Piliouras +7
We introduce -Rank, a principled evolutionary dynamics methodology for the evaluation and ranking of agents in large-scale multi-agent interactions, grounded in a novel dynamica…
Multi-agent Reinforcement Learning in Sequential Social Dilemmas
Joel Z. Leibo, Vinicius Zambaldi, Marc Lanctot +2
Matrix games like Prisoner's Dilemma have guided research on social dilemmas for decades. However, they necessarily treat the choice to cooperate or defect as an atomic action. In…