Hierarchical RL

RL: Reinforcement Learning

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Overview

Hierarchical reinforcement learning helps agents handle long tasks by grouping primitive actions into skills or planning through intermediate goals. Common approaches include options and manager-worker policies, learned subgoal selection, action chunking, offline skill reuse, and model-based planning. These methods are applied to sparse-reward control, robotics, multi-agent coordination, and language-model agents, where they can improve exploration, credit assignment, and transfer. A central challenge is learning abstractions that are useful and stable without hand-designed boundaries, while keeping high-level plans aligned with what low-level controllers can reliably execute.

Latest papers

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160 papers25 papers in the last four weeks, up 32% on the four weeks before. 0.1% of all new papers.

  1. Hierarchical RL-MPC Control for Dynamic Wake Steering in Wind Farms

    Apr 13, 2026Marcus Binder Nilsen, Teodor Olof Benedict Åstrand, Tuhfe Göçmen +1RL ControlModel Predictive Control

    Technical University of Denmark, Department of Wind and Energy Systems. Roskilde, Frederiksborgvej 399, Denmark

  2. Efficient Hierarchical Implicit Flow Q-learning for Offline Goal-conditioned Reinforcement Learning

    Apr 10, 2026Zhiqiang Dong, Teng Pang, Rongjian Xu +1Offline RLHierarchical RL

    School of Software, Shandong University, Jinan, Shandong, China · Luke EI, Jinan, China

  3. Smart Commander: A Hierarchical Reinforcement Learning Framework for Fleet-Level PHM Decision Optimization

    Apr 8, 2026Yong Si, Mingfei Lu, Jing Li +4Hierarchical RLPredictive Maintenance

    School of Aerospace Engineering, Tsinghua University, China · College of Information and Control Engineering, Xi’an University of Architecture and Technology, China · Hangzhou International Innovation Institute, Beihang University, China +2

  4. Predictive Representations for Skill Transfer in Reinforcement Learning

    Apr 8, 2026Ruben Vereecken, Luke Dickens, Alessandra RussoTransfer Learning in RLPredictive State Representations

    Computer Science, Imperial College, UK · Information Studies, UCL, UK

  5. HiPolicy: Hierarchical Multi-Frequency Action Chunking for Policy Learning

    Apr 7, 2026Jiyao Zhang, Zimu Han, Junhan Wang +7Policy LearningAction Chunking

    CFCS, School of CS, PKU · National Key Laboratory for Multimedia Information Processing, School of CS, PKU · XJTU +3

  6. Hierarchical Reinforcement Learning with Augmented Step-Level Transitions for LLM Agents

    Apr 7, 2026Shuai Zhen, Yanhua Yu, Ruopei Guo +2RL for LLM AgentsReinforcement Learning

    Beijing University of Posts and Telecommunications · China Mobile Group Design Institute Co., Ltd · Singapore Management University

  7. Learning to Focus: CSI-Free Hierarchical MARL for Reconfigurable Reflectors

    Apr 6, 2026Hieu Le, Mostafa Ibrahim, Oguz Bedir +2Reconfigurable Intelligent SurfacesHierarchical RL

    Electrical and Computer Engineering Texas A&M University College Station, Texas, USA · Engineering Technology and Industrial Distribution Texas A&M University College Station, Texas, USA · School of Performance, Visualization, and Fine Arts Texas A&M University College Station, Texas, USA

  8. DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data

    Apr 1, 2026Arshia Ilaty, Hossein Shirazi, Amir Rahmani +1Synthetic Tabular Data GenerationPrivacy-Preserving ML

    Computational Science Research Center, San Diego State University, San Diego, CA 92182 USA. · School of Nursing and Department of Computer Science, University of California, Irvine, CA 92697 USA. · Fowler College of Business, San Diego State University, San Diego, CA 92182 USA. +1

  9. Hierarchical Apprenticeship Learning from Imperfect Demonstrations with Evolving Rewards

    Mar 31, 2026Md Mirajul Islam, Rajesh Debnath, Adittya Soukarjya Saha +1Learning from Suboptimal DemonstrationsLearning from Demonstration

    North Carolina State University, Raleigh, NC 27606, USA

  10. Optimizing Resource-Constrained Non-Pharmaceutical Interventions for Multi-Cluster Outbreak Control Using Hierarchical Reinforcement Learning

    Mar 19, 2026Xueqiao Peng, Andrew PerraultHealthcareConstrained RL

    The Ohio State University

  11. ARISE: Agent Reasoning with Intrinsic Skill Evolution in Hierarchical Reinforcement Learning

    Mar 17, 2026Yu Li, Rui Miao, Zhengling Qi +1RL for Language Model ReasoningLLM Mathematical Reasoning

    Department of Electrical and Computer Engineering, George Washington University · Department of Mathematical Sciences, University of Texas at Dallas · School of Business, George Washington University

  12. EcoFair-CH-MARL: Scalable Constrained Hierarchical Multi-Agent RL with Real-Time Emission Budgets and Fairness Guarantees

    Mar 15, 2026Saad AlqithamiConstrained MARLMulti-Agent Reinforcement Learning

    Computer Science Department, Al-Baha University, Albaha 65779, Saudi Arabia

  13. SCALAR: Learning and Composing Skills through LLM Guided Symbolic Planning and Deep RL Grounding

    Mar 10, 2026Renos Zabounidis, Yue Wu, Simon Stepputtis +4LLM-Guided RLLLM Agent Skill Learning

    School of Computer Science, Carnegie Mellon University · Department of Mechanical Engineering, Virginia Tech

  14. Optimizing Reinforcement Learning Training over Digital Twin Enabled Multi-fidelity Networks

    Mar 9, 2026Hanzhi Yu, Hasan Farooq, Julien Forgeat +4Hierarchical RLDigital Twins

    Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33146 USA · Ericsson Research, Santa Clara, CA, 95054, USA · European AI Office, European Commission, Brussels, Belgium

  15. Multi-level meta-reinforcement learning with skill-based curriculum

    Mar 9, 2026Sichen Yang, Mauro MaggioniReinforcement LearningHierarchical RL

    Johns Hopkins University · Department of Applied Mathematics & Statistics Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA · Department of Mathematics, Department of Applied Mathematics & Statistics Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA

  16. Fibration Policy Optimization

    Mar 9, 2026Chang Li, Tshihao Tsu, Yaren Zhang +2Policy OptimizationRL for Language Models

    JD Explore Academy · Carleton University

  17. Helix: Evolutionary Reinforcement Learning for Open-Ended Scientific Problem Solving

    Mar 8, 2026Chang Su, Zhongkai Hao, Zhizhou Zhang +4Evolutionary RLReinforcement Learning

    Bosch (China) Investment Co., Ltd. · Tsinghua-Bosch Joint Center for ML, Tsinghua University · Dept. of Comp. Sci. & Techn., Tsinghua University +1

  18. Learning to Reflect: Hierarchical Multi-Agent Reinforcement Learning for CSI-Free mmWave Beam-Focusing

    Mar 7, 2026Hieu Le, Oguz Bedir, Mostafa Ibrahim +2Millimeter-Wave CommunicationsWireless Communications

    Texas A&M University

  19. Boosting deep Reinforcement Learning using pretraining with Logical Options

    Mar 6, 2026Zihan Ye, Phil Chau, Raban Emunds +5Neuro-Symbolic RLReinforcement Learning

    CS Department, Technical University of Darmstadt, Germany · AIML Group · Hessian AI +2

  20. Task-Level Decisions to Gait Level Control: A Hierarchical Policy Approach for Quadruped Navigation

    Mar 6, 2026Sijia Li, Haoyu Wang, Shenghai Yuan +2Quadruped Robot NavigationRobot Navigation

  21. MIRACL: A Diverse Meta-Reinforcement Learning for Multi-Objective Multi-Echelon Combinatorial Supply Chain Optimisation

    Mar 5, 2026Rifny Rachman, Josh Tingey, Richard Allmendinger +3Supply Chain OptimizationMulti-Objective Reinforcement Learning

    The University of Manchester, United Kingdom · Peak AI, Ltd, United Kingdom

  22. LLM-assisted Semantic Option Discovery for Facilitating Adaptive Deep Reinforcement Learning

    Mar 2, 2026Chang Yao, Jinghui Qin, Kebing Jin +1Reinforcement LearningLLM-Guided RL

  23. HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agents

    Mar 1, 2026Hongbo Jin, Rongpeng Zhu, Jiayu Ding +2Long-Horizon LLM AgentsLong-Horizon Agent Tasks

    School of Electronic and Computer Engineering, Peking University

  24. Intent-Context Synergy Reinforcement Learning for Autonomous UAV Decision-Making in Air Combat

    Mar 1, 2026Jiahao Fu, Feng YangReinforcement LearningPartially Observable RL

    National Elite Institute of Engineering,Northwestern Polytechnical University, Xi’an, Shanxi, China · School of Automation, Northwestern Polytechnical University, Xi’an, Shanxi, China

  25. HierKick: Hierarchical Reinforcement Learning for Vision-Guided Soccer Robot Control

    Mar 1, 2026Yizhi Chen, Zheng Zhang, Zhanxiang Cao +7Robotic ControlRobotic RL

    Tongji University, Shanghai, China. · Shanghai Innovation Institute, Shanghai, China. · Shanghai Jiao Tong University, Shanghai, China. +2

  26. Hierarchical Lead Critic based Multi-Agent Reinforcement Learning

    Feb 25, 2026David Eckel, Henri MeeßMulti-Agent Reinforcement LearningCooperative MARL

    Fraunhofer Institute IVI, Ingolstadt, Germany

  27. In-Context Planning with Latent Temporal Abstractions

    Feb 21, 2026Baiting Luo, Yunuo Zhang, Nathaniel S. Keplinger +3Model-Based PlanningOffline RL

    Vanderbilt University · William & Mary

  28. Toward AI Autonomous Navigation for Mechanical Thrombectomy using Hierarchical Modular Multi-agent Reinforcement Learning (HM-MARL)

    Feb 20, 2026Harry Robertshaw, Nikola Fischer, Lennart Karstensen +6Robotic Endovascular InterventionMulti-Agent Reinforcement Learning

    School of Biomedical Engineering & Imaging Sciences, Kings College London, London, UK · School of Engineering & Materials Science, Queen Mary University of London, London, UK

  29. Hierarchical Reward Design from Language: Enhancing Alignment of Agent Behavior with Human Specifications

    Feb 20, 2026Zhiqin Qian, Ryan Diaz, Sangwon Seo +1Reward Design for RLAI Alignment

    Rice University, Houston, TX, USA

  30. A Scalable Approach to Solving Simulation-Based Network Security Games

    Feb 18, 2026Michael Lanier, Yevgeniy VorobeychikMulti-Agent Reinforcement LearningHierarchical RL