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About this paper
Zuo Gou, Chenhao Lu
The authors introduce a step ledger to check whether reinforcement-learning environments and trainers exchange the intended data. The ledger records what each side sends and receives and compares records step by step. In tested tasks it caught every injected boundary fault, with 3% median training-time overhead on Pendulum. Tests covered simulated environments and one trainer.
Summary by alphaXiv.
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