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Reinforcement learning with human advice: a survey

arXiv 2005.11016 ↗First posted 22 May 2020cs.AIcited by 23

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Abstract (arXiv)

In this paper, we provide an overview of the existing methods for integrating human advice into a Reinforcement Learning process. We first propose a taxonomy of the different forms of advice that can be provided to a learning agent. We then describe the methods that can be used for interpreting advice when its meaning is not determined beforehand. Finally, we review different approaches for integrating advice into the learning process.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 May 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 4; 2023: 7; 2024: 4; 2025: 5; 2026: 2.

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  1. 2025A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Futurecited by 53
  2. 2023Prompt Engineering for Healthcare: Methodologies and Applicationscited by 52
  3. 2023Perspectives on the Social Impacts of Reinforcement Learning with Human Feedbackcited by 15
  4. 2023Decision Making for Human-in-the-loop Robotic Agents via Uncertainty-Aware Reinforcement Learningcited by 9
  5. 2023Hybrid Approaches for Moral Value Alignment in AI Agents: a Manifestocited by 7
  6. 2022Good Time to Ask: A Learning Framework for Asking for Help in Embodied Visual Navigationcited by 3
  7. 2023CROP: Towards Distributional-Shift Robust Reinforcement Learning using Compact Reshaped Observation Processingcited by 3
  8. 2023Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Gamescited by 3
  9. 2024On Bits and Bandits: Quantifying the Regret-Information Trade-offcited by 3
  10. 2024Opinion-Guided Reinforcement Learningcited by 3
  11. 2024Towards Sample-Efficiency and Generalization of Transfer and Inverse Reinforcement Learning: A Comprehensive Literature Reviewcited by 3
  12. 2025Interactive Imitation Learning for Dexterous Robotic Manipulation: Challenges and Perspectives -- A Surveycited by 3
11 more
  1. 2021Towards Interactive Reinforcement Learning with Intrinsic Feedbackcited by 2
  2. 2025Complex Model Transformations by Reinforcement Learning with Uncertain Human Guidancecited by 2
  3. 2025Interactive Program Synthesis for Modeling Collaborative Physical Activities from Narrated Demonstrationscited by 2
  4. 2022Modeling Human Behavior Part II -- Cognitive approaches and Uncertaintycited by 1
  5. 2022Modeling Human Behavior Part I -- Learning and Belief Approachescited by 1
  6. 2022Contextualizing Artificially Intelligent Morality: A Meta-Ethnography of Top-Down, Bottom-Up, and Hybrid Models for Theoretical and Applied Ethics in Artificial Intelligencecited by 0
  7. 2023Optimal Transport for Correctional Learningcited by 0
  8. 2024Adaptive Querying for Reward Learning from Human Feedbackcited by 0
  9. 2025Robots and Children that Learn Together : Improving Knowledge Retention by Teaching Peer-Like Interactive Robotscited by 0
  10. 2026Feedback Manipulation Regularization: Enabling Offline Agent Alignment for Imitation Learningcited by 0
  11. 2026Inference-Time Policy Alignment for Fair Reinforcement Learningcited by 0