arXiv Machine Learning June 30, 2026 By Yuexuan Wang, Jingyuan Zhou, Kaidi Yang

Hierarchical Decision Making with Structured Policies: A Principled Design via Inverse Optimization

Read the original on arXiv Machine Learning →

arXiv:2606. 28764v1 Announce Type: new Abstract: Hierarchical decision-making frameworks are pivotal for addressing complex control tasks, enabling agents to decompose intricate problems into manageable subgoals.

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arXiv Machine Learning

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HERAKLES: Hierarchical Skill Compilation for Open-ended LLM Agents

arXiv:2508. 14751v2 Announce Type: replace Abstract: We study goal-conditioned reinforcement learning in partially observable environments with sparse rewards and large, structured goal spaces.

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Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning

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arXiv Machine Learning

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arXiv Machine Learning

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Offline RL with Hierarchical Action Chunking

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