Scalable Efficient Deep-RL

A more efficient way to scale up reinforcement learning algorithms

Sherwin Chen
Nov 7 · 4 min read

Introduction

Traditional scalable reinforcement learning framework, such as IMPALA and R2D2, runs multiple agents in parallel to collect transitions, each with its own copy of model from the parameter server(or learner). This architecture imposes high bandwidth requirements…

Sherwin Chen

Written by

A learner, interested in deep learning and reinforcement learning.

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