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Raphaël Marinier

2 accepted papers

2021

What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study

ICLR 2021oral

In recent years, reinforcement learning (RL) has been successfully applied to many different continuous control tasks. While RL algorithms are often conceptually simple, their state-of-the-art implementations take numerous low- and high-level design decisions that strongly affect the performance of…

Cited by 230SourcePDFScholar
2020

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference

ICLR 2020talk

We present a modern scalable reinforcement learning agent called SEED (Scalable, Efficient Deep-RL). By effectively utilizing modern accelerators, we show that it is not only possible to train on millions of frames per second but also to lower the cost. of experiments compared to current methods. We…

Cited by 166SourcecodeScholar