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Realizable abstractions: Near-optimal hierarchical reinforcement learning · 2018 · arXiv 2512.04958

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Skill Reuse as Compression in Agentic RL

cs.LG · 2026-05-29 · unverdicted · novelty 5.0

ReuseRL augments agentic RL with an MDL-based compression penalty on skill reuse, proves a PAC-Bayes bound, and reports higher in- and out-of-distribution success on ALFWorld, TextWorld-Cooking, and Countdown-Stepwise versus GRPO and round-length baselines.

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  • Skill Reuse as Compression in Agentic RL cs.LG · 2026-05-29 · unverdicted · none · ref 1

    ReuseRL augments agentic RL with an MDL-based compression penalty on skill reuse, proves a PAC-Bayes bound, and reports higher in- and out-of-distribution success on ALFWorld, TextWorld-Cooking, and Countdown-Stepwise versus GRPO and round-length baselines.