SEED RL

Reinforcement LearningIntroduced 20002 papers
Source Paper

Description

SEED (Scalable, Efficient, Deep-RL) is a scalable reinforcement learning agent. It utilizes an architecture that features centralized inference and an optimized communication layer. SEED adopts two state of the art distributed algorithms, IMPALA/V-trace (policy gradients) and R2D2 (Q-learning).

Papers Using This Method

VALAN: Vision and Language Agent Navigation2019-12-06SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference2019-10-15