Meta-Reinforcement Learning

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Overview

Meta-reinforcement learning studies how an agent can use experience across many related tasks to learn a new task with little additional interaction. Common approaches include gradient-based methods such as MAML, recurrent or context-conditioned policies that infer tasks from interaction histories, and Bayesian or world-model methods that represent task uncertainty and predict outcomes. Researchers also use hierarchical skills, population-based search, and language or reflection signals to support adaptation in settings from robot control to multi-agent games and language agents. A central challenge is making adaptation generalize to unfamiliar task distributions while remaining data-efficient and safe, especially when task context is ambiguous or learned models are unreliable.

Latest papers

CardsList

40 papers4 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. METTA: Memory-Enhanced Test-Time Adaptation for Meta-Reinforcement Learning

    Oct 22, 2026Ali Najar, Hosein Hasani, Amir Kooshan Fattah +2Meta-Reinforcement LearningTest-Time RL

    Department of Computer Engineering Sharif University of Technology

  2. Pessimistic Latent Task-aware Optimization for Robust Offline Meta-Reinforcement Learning

    Oct 11, 2026Chang-Hoon Jeong, Kisung Shin, Hanwool Sul +1Meta-Reinforcement LearningOOD Generalization

    Dept. of Computer Science and Engineering, Seoul National University · Interdisciplinary Program in Artificial Intelligence, Seoul National University

  3. Multi-Agent Spectrum Sharing

    Oct 3, 2026Job Elliott, Graduate Student Member, IEEE +2Wireless Resource AllocationMulti-Agent Systems

  4. Meta-Multi-Agent Reinforcement Learning for Fast Adaptation of Interactive Policies with Applications to Autonomous Driving

    Sep 30, 2026Huiwen Yan, Kyriakos G. Vamvoudakis, Mushuang LiuMeta-Reinforcement LearningRL for Autonomous Driving

    Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA 24061, USA · Daniel Guggenheim School of Aerospace Engineering, Georgia Tech, Atlanta, GA 30332, USA

  5. Personalized Federated Reinforcement Learning via Model-Agnostic Meta-Learning: Convergence of Exact and Hessian-Free Meta-Policy Gradients

    Sep 19, 2026Ali Beikmohammadi, Sarit Khirirat, Sindri MagnússonFederated RLMeta-Learning

    Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden. · Faculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.

  6. The Free Inference Dimension: Complexity Measure for Zero-Collision Navigation under Hypothesis Mixtures

    Sep 15, 2026Luiz Carlos Castro Guedes, Edward Hermann HaeuslerReinforcement LearningMeta-Reinforcement Learning

    Departamento de Informática – PUC-Rio, Brazil · Seção de Engenharia de Computação – Instituto Militar de Engenharia, Brazil

  7. Fast-Convergent Meta-RL via Gradient-Clustered BS Sampling for Edge Caching

    Sep 14, 2026Farnaz Niknia, Ping WangEdge ComputingMeta-Reinforcement Learning

    Lassonde School of Engineering at York University, Toronto, ON, M3J 1P3, Canada

  8. Safe Meta-Reinforcement Learning via Information Space Reachability

    Sep 14, 2026Zeyang Li, Sunbochen Tang, Navid AzizanReachability AnalysisConstrained RL

    Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA 02139, USA

  9. Does Latent Context Help? A Controlled Evaluation of Inverse Reinforcement Learning in Arctic Shipping

    Aug 6, 2026Vaishnav Vaidheeswaran, Dilith Jayakody, Biruk Ambaw +3Reinforcement LearningMeta-Reinforcement Learning

    Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada · Department of Industrial Engineering, Faculty of Engineering, Dalhousie University, Halifax, NS, Canada

  10. From Trajectories to Instructions: Language-Conditioned Meta-Reinforcement Learning

    Jul 21, 2026Garvit Singla, Uma Maheswari Natarajan, Raghuram Bharadwaj DiddigiReinforcement LearningMeta-Learning

    International Institute of Information Technology Bangalore, India

  11. Quasi-Monte Carlo Initialization for Meta-Reinforcement Learning

    Jul 21, 2026Julian G. SoltesNeural Network InitializationMeta-Reinforcement Learning

    Regis University, USA

  12. Neuro-Symbolic Meta-Policies for Temporal Knowledge-Graph Memory under Partial Observability

    Jul 20, 2026Taewoon Kim, Vincent François-Lavet, Michael CochezReinforcement LearningPartially Observable RL

    HumemAI, The Netherlands · Vrije Universiteit Amsterdam, The Netherlands · ELLIS Institute Finland & Abo Akademi University, Finland

  13. Meta-Reinforcement Learning via Evolution for Multi-Objective Combinatorial Supply Chain Optimisation

    Jun 20, 2026Rifny Rachman, Bahrul Ilmi Nasution, Josh Tingey +3Multi-Objective Reinforcement LearningMulti-Objective Evolutionary Optimization

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

  14. Knowledge Reutilization in Meta-Reinforcement Learning

    Jun 16, 2026Yuan Meng, Bo Wang, Juan de los Rios Ruiz +4Cross-Embodiment Robot LearningMeta-Reinforcement Learning

    School of Computation, Information and Technology, Technical University of Munich, Munich, Germany · State Key Laboratory for Novel Software Technology, Nanjing University, Suzhou, China · Department of Computer Science and Technology, Tsinghua University, Beijing, China

  15. Memory-Efficient Meta-Reinforcement Learning for Adaptive Safety-Critical Control in Adversarial Spacecraft Proximity Operations

    Jun 16, 2026Alejandro Posadas-Nava, Richard Linares, Minduli WijayatungaSpacecraft Rendezvous and Proximity OperationsControl Barrier Functions

    Researcher, AeroAstro, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139-4307. · Associate Professor and Rockwell International Career Development Professor, AeroAstro, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139-4307. · Assistant Professor, Department of Aerospace Engineering, University of Illinois, Urbana-Champaign, 104 S Wright St, Urbana, IL 61801.

  16. Autonomous Aerial Manipulation via Contextual Contrastive Meta Reinforcement Learning

    Jun 7, 2026Lixuan Jin, Bingxuan Lan, Xinyi Bao +9Meta-Reinforcement LearningAerial Manipulation

    National Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, China · School of Artificial Intelligence, Nanjing University, Nanjing, China · Faculty of Robot Science and Engineering, Northeastern University, China +1

  17. Decoupled Behavioral Cloning for Scalable Inductive Generalization in RL from Specifications

    May 30, 2026Vignesh Subramanian, Subhajit Roy, Suguman BansalReinforcement LearningMeta-Reinforcement Learning

    School of Computer Science, Georgia Institute of Technology, USA · Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, India

  18. Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning

    May 30, 2026Fuyuan Qian, Menglong Zhang, Song Wang +1Representation LearningOffline RL

    Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China · AI Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China · Omni-Intelligence, Shenzhen, Guangdong, China +1

  19. Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment

    May 26, 2026Gengyue Han, Yiheng FengReinforcement LearningSim-to-Real Transfer

    Lyles School of Civil and Construction Engineering, Purdue University, West Lafayette, USA · Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA

  20. ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning

    May 19, 2026Yuan Zhao, Youwei Pang, Jiaming Zuo +10Image SegmentationPromptable Image Segmentation

    1Dalian University of Technology, China · 3Nanyang Technological University, Singapore · 2X3000 Inspection Co., Ltd +3

  21. Heterogeneous Tasks Offloading in Vehicular Edge Computing: A Federated Meta Deep Reinforcement Learning Approach

    May 18, 2026Yaorong Huang, Jingtao Luo, Xuechao WangFederated RLEdge Computing

    ∗The Hong Kong University of Science and Technology (Guangzhou) · †Chengdu Neusoft University

  22. MATE: Solving Contextual Markov Decision Processes with Memory of Accumulated Transition Embeddings

    May 17, 2026Himchan Hwang, Hyeokju Jeong, Gene Chung +3Markov Decision ProcessesMeta-Reinforcement Learning

    Seoul National University · Saige · Ulsan National Institute of Science and Technology (UNIST)

  23. RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards

    May 11, 2026Gaotang Li, Bhavana Dalvi Mishra, Zifeng Wang +9Reinforcement LearningRubric-Based RL

    University of Illinois Urbana-Champaign · Google Cloud AI Research

  24. A Meta Reinforcement Learning Approach to Goals-Based Wealth Management

    May 4, 2026Sanjiv R. Das, Harshad Khadilkar, Sukrit Mittal +3Financial ServicesMeta-Learning

    Dept. of Finance, Santa Clara University, Santa Clara, CA, USA · Indian Institute of Technology, Mumbai, India · Franklin Templeton, Mumbai, India +4

  25. VA-FastNavi-MARL: Real-Time Robot Control with Multimedia-Driven Meta-Reinforcement Learning

    Apr 5, 2026Yang Zhang, Shengxi Jing, Fengxiang Wang +2Real-Time Robot ControlRobotic Control

    Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65201, USA · School of Construction Machinery, Chang’an University, Xi’an, 710064, Shaanxi, China · School of Artificial Intelligence, Hubei University, Wuhan, 430062, Hubei, China +1

  26. Unified Policy Value Decomposition for Rapid Adaptation

    Mar 18, 2026Cristiano Capone, Luca Falorsi, Andrea Ciardiello +1Zero-Shot RLReinforcement Learning

    Computational Neuroscience Unit, Istituto Superiore di Sanit`a, 00161, Rome, Italy · Ospedale Santa Lucia, Rome, Italy · School of Computer Science, University of Sheffield,Sheffield,S10 2TN, United Kingdom

  27. Meta-Reinforcement Learning with Self-Reflection for Agentic Search

    Mar 11, 2026Teng Xiao, Yige Yuan, Hamish Ivison +6Reinforcement LearningAgentic Search

    Allen Institute for AI · University of Washington · Independent

  28. MAVEN: A Meta-Reinforcement Learning Framework for Varying-Dynamics Expertise in Agile Quadrotor Maneuvers

    Mar 11, 2026Jin Zhou, Dongcheng Cao, Xian Wang +1Robot Policy AdaptationQuadrotor Control

    Authors are with the College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China

  29. 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

  30. Meta-RL with Shared Representations Enables Fast Adaptation in Energy Systems

    Mar 9, 2026Théo Zangato, Aomar Osmani, Pegah AlizadehMeta-Reinforcement LearningMulti-Task RL

    Université Sorbonne Paris Nord, France · INSA Rouen, France · Université Lumière Lyon 2, Université Claude Bernard Lyon 1, ERIC, 69007, Lyon, France