Public training checkpoints and scalar learning curves for ten CSP research runs (Push-T, Reacher, Cube and Two-Room). Experimental models, not a claim of benchmark success or production readiness. One training seed per configuration. Each runs/ /config.json records the scientific settings. latest.json identifies the current and previous complete resume states and their SHA256s. Resume files include neural modules, optimizers, SIGReg buffers, RNG states, module modes and training position. They intentionally omit original filesystem paths and credentials. A transport adapter restores the locally pinned config and source identity before invoking the unchanged native trainer. Weights-only…
Independent publisher
Yiyang Du
yiyangd
Models in Library1
Datasets in Library0
Models on Hugging Face102
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Published tasks: Reinforcement learning.
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