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

ICLR 2020 Lasse EspeholtRaphaël MarinierPiotr StanczykKe WangMarcin Michalski

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... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.