mlsanityData to 14 Oct 2026

Reinforcement learning

arXiv 2405.10369 ↗First posted 16 May 2024astro-ph.IM cs.AI cs.LGcited by 247

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

Observing celestial objects and advancing our scientific knowledge about them involves tedious planning, scheduling, data collection and data post-processing. Many of these operational aspects of astronomy are guided and executed by expert astronomers. Reinforcement learning is a mechanism where we (as humans and astronomers) can teach agents of artificial intelligence to perform some of these tedious tasks. In this paper, we will present a state of the art overview of reinforcement learning and how it can benefit astronomy.

Key facts. Cited by 247 papers in the map (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 0 of its 151 references that are in the map. First posted on arXiv 16 May 2024.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 64; 2025: 110; 2026: 73.

247 papers.

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  1. 2025Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learningcited by 1,444
  2. 2025Training Language Models to Reason Efficientlycited by 247
  3. 2025ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learningcited by 161
  4. 2025Multi-Agent Collaboration via Evolving Orchestrationcited by 108
  5. 2025AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learningcited by 72
  6. 2025VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learningcited by 68
  7. 2024UltraMedical: Building Specialized Generalists in Biomedicinecited by 67
  8. 2026Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisonscited by 60
  9. 2024Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTScited by 54
  10. 2025ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understandingcited by 50
  11. 2024Diffusion Policies creating a Trust Region for Offline Reinforcement Learningcited by 43
  12. 2025BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulationcited by 43
38 more
  1. 2025FlowRL: Matching Reward Distributions for LLM Reasoningcited by 40
  2. 2025Flow-Based Policy for Online Reinforcement Learningcited by 37
  3. 2024Agents Thinking Fast and Slow: A Talker-Reasoner Architecturecited by 36
  4. 2026Maximum Likelihood Reinforcement Learningcited by 36
  5. 2025MemSearcher: Training LLMs to Reason, Search and Manage Memory via End-to-End Reinforcement Learningcited by 27
  6. 2025O2-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answeringcited by 23
  7. 2025MO-GRPO: Mitigating Reward Hacking of Group Relative Policy Optimization on Multi-Objective Problemscited by 23
  8. 2024SAIL: Self-Improving Efficient Online Alignment of Large Language Modelscited by 20
  9. 2026Diversity-Preserved Distribution Matching Distillation for Fast Visual Synthesiscited by 20
  10. 2024Dynamic Fraud Detection: Integrating Reinforcement Learning into Graph Neural Networkscited by 19
  11. 2024Foundations of Multivariate Distributional Reinforcement Learningcited by 17
  12. 2024Autonomous Agents for Collaborative Task under Information Asymmetrycited by 16
  13. 2025When Thinking Drifts: Evidential Grounding for Robust Video Reasoningcited by 16
  14. 2024Graph Neural Networks for Job Shop Scheduling Problems: A Surveycited by 15
  15. 2025Co-Reinforcement Learning for Unified Multimodal Understanding and Generationcited by 15
  16. 2024A transfer learning framework for weak-to-strong generalizationcited by 14
  17. 2024Quantum-Train-Based Distributed Multi-Agent Reinforcement Learningcited by 14
  18. 2025Reconstructing 4D Spatial Intelligence: A Surveycited by 14
  19. 2026On-the-Fly VLA Adaptation via Test-Time Reinforcement Learningcited by 14
  20. 2025ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMscited by 13
  21. 2025Controlling Performance and Budget of a Centralized Multi-agent LLM System with Reinforcement Learningcited by 13
  22. 2024Automated radiotherapy treatment planning guided by GPT-4Visioncited by 12
  23. 2025Data-Efficient RLVR via Off-Policy Influence Guidancecited by 12
  24. 2026Spark: Strategic Policy-Aware Exploration via Dynamic Branching for Long-Horizon Agentic Learningcited by 11
  25. 2025Benchmarking Quantum Reinforcement Learningcited by 10
  26. 2025Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learningcited by 10
  27. 2024Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewardscited by 9
  28. 2025Research on the Design of a Short Video Recommendation System Based on Multimodal Information and Differential Privacycited by 9
  29. 2026GeoEyes: On-Demand Visual Focusing for Evidence-Grounded Understanding of Ultra-High-Resolution Remote Sensing Imagerycited by 9
  30. 2025User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Datacited by 8
  31. 2025ProRefine: Inference-Time Prompt Refinement with Textual Feedbackcited by 8
  32. 2025H2R: Hierarchical Hindsight Reflection for Multi-Task LLM Agentscited by 8
  33. 2024Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for Few-Shot Class-Incremental Learningcited by 7
  34. 2025Collective Reasoning Among LLMs: A Framework for Answer Validation Without Ground Truthcited by 7
  35. 2025RLCAD: Reinforcement Learning Training Gym for Revolution Involved CAD Command Sequence Generationcited by 7
  36. 2024Learning to Play Atari in a World of Tokenscited by 6
  37. 2024Systematic Literature Review on Application of Learning-based Approaches in Continuous Integrationcited by 6
  38. 2024Enhancing Answer Reliability Through Inter-Model Consensus of Large Language Modelscited by 6

50 most cited of 247 All 247 (JSON)

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  1. 2025Solving Online Resource-Constrained Scheduling for Follow-Up Observation in Astronomy: a Reinforcement Learning Approach
  2. 2023Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning
  3. 2025Learning-Based Planning for Improving Science Return of Earth Observation Satellites
  4. 2024Reinforcement Learning for Data-Driven Workflows in Radio Interferometry. I. Principal Demonstration in Calibration
  5. 2026On-sky demonstration of reinforcement learning for adaptive optics control
  6. 2025On the Role of AI in Managing Satellite Constellations: Insights from the ConstellAI Project
  7. 2025Investigating the Impact of Observation Space Design Choices On Training Reinforcement Learning Solutions for Spacecraft Problems
  8. 2024Deep Reinforcement Learning for Scalable Multiagent Spacecraft Inspection