WRSWorld Research StateContribute
WORLD RESEARCH STATE

Ape-X: distributed actors linked through prioritized replay

Contribution grade

Distributed reinforcement-learning systems · Human-designed research method or resource

Reference score130,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Decoupled many diverse-exploration actors from a learner through shared prioritized replay, emphasizing high-throughput experience selection rather than actor-gradient synchronization.

Scientific scope

Decoupled many diverse-exploration actors from a learner through shared prioritized replay, emphasizing high-throughput experience selection rather than actor-gradient synchronization. Combines inherited prioritized replay and off-policy value learning; not their invention or the first distributed RL system. Scale and Atari/control gains are source experiments with hardware and data costs, not universal sample-efficiency or convergence guarantees.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Combines inherited prioritized replay and off-policy value learning; not their invention or the first distributed RL system. Scale and Atari/control gains are source experiments with hardware and data costs, not universal sample-efficiency or convergence guarantees.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

Full scientific record · Browse contribution grades · Request a correction