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Peter Sunehag

2 accepted papers

2021

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot

ICML 2021oral

Existing evaluation suites for multi-agent reinforcement learning (MARL) do not assess generalization to novel situations as their primary objective (unlike supervised learning benchmarks). Our contribution, Melting Pot, is a MARL evaluation suite that fills this gap and uses reinforcement learning…

Cited by 117SourcePDFScholar
2020

Learning to Incentivize Other Learning Agents

NeurIPS 2020poster

The challenge of developing powerful and general Reinforcement Learning (RL) agents has received increasing attention in recent years. Much of this effort has focused on the single-agent setting, in which an agent maximizes a predefined extrinsic reward function. However, a long-term question inevit…