PRL framework adds adaptive concurrency to boost RL training efficiency
samsja19 · x · 2026-08-20
The open-source reinforcement learning framework PRL has released an "adaptive concurrency" feature. This dynamically adjusts in-flight rollouts to maximize throughput, which is crucial for scaling sub-agent and multi-agent training. It means RL runs can utilize 100% of inference capacity out of the box without manual tuning or hyperparameters, significantly saving time and lowering the barrier to entry.
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