Reward Design for RL

RL: Reinforcement Learning

Ask about this topic

Overview

Reward design studies how to turn task goals, preferences, and constraints into learning signals, especially when success is sparse or objectives compete. Approaches include potential-based shaping and reward machines, preference and rubric models, visual progress rewards, intrinsic exploration bonuses, and automated reward search using language models. These methods are used in settings from robot manipulation and locomotion to language-model reasoning, tool use, and multi-agent coordination. A central tension is that denser or adaptive rewards can improve credit assignment but also mislead policies, destabilize training, or invite reward hacking, so evaluation must test intended outcomes rather than proxy scores alone.

Latest papers

CardsList

261 papers44 papers in the last four weeks, up 83% on the four weeks before. 0.3% of all new papers.

  1. Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents

    Mar 13, 2026Jiawei Huang, Qingping Yang, Renjie Zheng +1Software Engineering AgentsReward Design for RL

    ETH Zurich · ByteDance Seed

  2. Hybrid Energy-Aware Reward Shaping: A Unified Lightweight Physics-Guided Methodology for Policy Optimization

    Mar 12, 2026Qijun Liao, Jue Yang, Yiting Kang +3RL ControlReinforcement Learning

    School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China · Jiangsu XCMG Construction Machinery Research Institute Co., Ltd., Jiangsu 221000, China

  3. Learning to Score: Tuning Cluster Schedulers through Reinforcement Learning

    Mar 11, 2026Martin Asenov, Qiwen Deng, Gingfung Yeung +1Learning to OptimizeReinforcement Learning

    Edinburgh Research Centre, Central Software Institute, Huawei · School of Computer Science, University of St Andrews

  4. Impact of Markov Decision Process Design on Sim-to-Real Reinforcement Learning

    Mar 10, 2026Tatjana Krau, Jorge Mandlmaier, Tobias Damm +1Sim-to-Real TransferMarkov Decision Processes

    Institute of Production and Informatics, 87527 Sonthofen, Germany · Department of Mathematics, RPTU University Kaiserslautern-Landau, 67663 Kaiserslautern, Germany

  5. Reward-Zero: Language Embedding Driven Implicit Reward Mechanisms for Reinforcement Learning

    Mar 10, 2026Heng Zhang, Haddy Alchaer, Arash Ajoudani +1Reward Design for RLDense Reward RL

    Human-Robot Interfaces and Interaction Lab, Istituto Italiano di Tecnologia, Genova, Italy · Ph.D. program of national interest in Robotics and Intelligent Machines (DRIM) and Universit ‘a di Genova, Genoa, Italy. · Edwardson School of Industrial Engineering, Purdue University, West Lafayette, IN, USA. +2

  6. CODA: Difficulty-Aware Compute Allocation for Adaptive Reasoning

    Mar 9, 2026Siye Wu, Jian Xie, Yikai Zhang +1Adaptive Reasoning in Language ModelsAdaptive Computation

    ♠Fudan University

  7. Decoupling Task and Behavior: A Two-Stage Reward Curriculum in Reinforcement Learning for Robotics

    Mar 5, 2026Kilian Freitag, Knut Åkesson, Morteza Haghir ChehreghaniRL for RoboticsReinforcement Learning

    Chalmers University of Technology · Gothenburg University

  8. ToolRLA: Multiplicative Reward Decomposition for Tool-Integrated Agents

    Mar 2, 2026Pengbo LiuReward DecompositionTool-Using Agents

    Unaffiliated

  9. RLAR: An Agentic Reward System for Multi-task Reinforcement Learning on Large Language Models

    Feb 28, 2026Andrew Zhuoer Feng, Cunxiang Wang, Bosi Wen +4RL for Language ModelsReward Design for RL

    Tsinghua Univeristy · Peking University

  10. Keyframe-Guided Structured Rewards for Reinforcement Learning in Long-Horizon Laboratory Robotics

    Feb 28, 2026Yibo Qiu, Shu'ang Sun, Haoliang Ye +2Long-Horizon Robotic ManipulationRobotic RL

    Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu, China · School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China

  11. Adaptive Correlation-Weighted Intrinsic Rewards for Reinforcement Learning

    Feb 27, 2026Viet Bac Nguyen, Phuong Thai NguyenIntrinsic Reward MethodsReward Design for RL

    Institute for Artificial Intelligence, VNU-University of Engineering and Technology, Hanoi, Vietnam

  12. RF-Agent: Automated Reward Function Design via Language Agent Tree Search

    Feb 27, 2026Ning Gao, Xiuhui Zhang, Xingyu Jiang +3Reward Design for RLRL Control

    Beihang University, 37 Xueyuan Road, Haidian District, Beijing

  13. SibylSense: Adaptive Rubric Learning via Memory Tuning and Adversarial Probing

    Feb 24, 2026Yifei Xu, Guilherme Potje, Shivam Shandilya +9Rubric-Based RLReward Design for RL

    Microsoft · University of California, Los Angeles

  14. How to Train Your Deep Research Agent? Prompt, Reward, and Policy Optimization in Search-R1

    Feb 23, 2026Yinuo Xu, Shuo Lu, Jianjie Cheng +5RL for LLM AgentsAutonomous Research Agents

    NLPR & MAIS, CASIA · School of AI, UCAS · Meituan Inc.

  15. 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

  16. PRISM: Parallel Reward Integration with Symmetry for MORL

    Feb 20, 2026Finn van der Knaap, Kejiang Qian, Zheng Xu +1Equivariant Policy LearningReinforcement Learning

    University of Edinburgh · Meta Superintelligence Labs.

  17. Fairness over Equality: Correcting Social Incentives in Asymmetric Sequential Social Dilemmas

    Feb 17, 2026Alper Demir, Hüseyin Aydın, Kale-ab Abebe Tessera +2Cooperative MARLMulti-Agent Reinforcement Learning

    Izmir University of Economics & University of Edinburgh, Izmir, Turkey · Middle East Technical University & Utrecht University, Ankara, Turkey · University of Edinburgh, Edinburgh, United Kingdom +1

  18. Interactionless Inverse Reinforcement Learning: A Data-Centric Framework for Durable Alignment

    Feb 16, 2026Elias Malomgré, Pieter SimoensAI AlignmentReinforcement Learning

    IDLab, Ghent University - imec, Ghent, Belgium

  19. Dual-Evolving Reinforcement Learning for Automated Reward Design

    Dec 15, 2025Sitao Cheng, Tianle Li, Xuhan Huang +2Reward Design for RLReinforcement Learning

    University of Waterloo · The University of Hong Kong · The Chinese University of Hong Kong, Shenzhen +1

  20. Reinforcement Learning for Long-Horizon Unordered Tasks: From Boolean to Coupled Reward Machines

    Oct 31, 2025Kristina Levina, Nikolaos Pappas, Athanasios Karapantelakis +2Reinforcement LearningQ-Learning

    Linköping University, Linköping, Sweden · Ericsson Research, Stockholm, Sweden

  21. Gain Tuning Is Not What You Need: Reward Gain Adaptation for Constrained Locomotion Learning

    Oct 12, 2025Arthicha Srisuchinnawong, Poramate ManoonpongConstrained RLRL for Legged Locomotion

    Vidyasirimedhi Institute of Science and Technology, Rayong, Thailand. · The University of Southern Denmark, Odense, Denmark.