Search Results for author:
Found 2 papers, 2 papers with code
RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning
We introduce RLDS (Reinforcement Learning Datasets), an ecosystem for recording, replaying, manipulating, annotating and sharing data in the context of Sequential Decision Making (SDM) including Reinforcement Learning (RL), Learning from Demonstrations, Offline RL or Imitation Learning.
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference
We present a modern scalable reinforcement learning agent called SEED (Scalable, Efficient Deep-RL).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
