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20212026
most citedRAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning

19 citations · 37 across the 22 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

cs.LG2023★ 2 cited

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX

Alexander Rutherford, Benjamin Ellis, Matteo Gallici +18

Benchmarks are crucial in the development of machine learning algorithms, with available environments significantly influencing reinforcement learning (RL) research. Traditionally,…

cs.LG2023★ 3 cited

DITTO: Offline Imitation Learning with World Models

Branton DeMoss, Paul Duckworth, Jakob Foerster +2

For imitation learning algorithms to scale to real-world challenges, they must handle high-dimensional observations, offline learning, and policy-induced covariate-shift. We propos…