Distributed Reinforcement Learning

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).

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


Paper Code Results Date Stars


Task Papers Share
Reinforcement Learning (RL) 1 50.00%
Vision and Language Navigation 1 50.00%


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign