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Richard Everett

2 accepted papers

2021

Collaborating with Humans without Human Data

NeurIPS 2021spotlight

Collaborating with humans requires rapidly adapting to their individual strengths, weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement learning techniques, such as self-play (SP) or population play (PP), produce agents that overfit to their training partners and do no…

Cited by 201SourcePDFScholar
2020

Learning to Play No-Press Diplomacy with Best Response Policy Iteration

NeurIPS 2020spotlight

Recent advances in deep reinforcement learning (RL) have led to considerable progress in many 2-player zero-sum games, such as Go, Poker and Starcraft. The purely adversarial nature of such games allows for conceptually simple and principled application of RL methods. However real-world settings are…