SEED RL

2000년 도입 · 논문 2편에서 사용

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).

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

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