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 InferencePaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Reinforcement Learning (RL) | 1 | 50.00% |
Vision and Language Navigation | 1 | 50.00% |
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