强化学习论文趋势 2023–2026

策略优化、离线 RL 与基于环境的决策学习

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 6,885 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

强化学习论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023484233297561,070
2024466304356641,190
2025784379405721,640
20267609111,0212932,985

代表论文

按年份和会议均匀挑选,方便快速看到每一届的样貌

全部强化学习论文

共 6,885 篇,第 122 / 138 页

  1. ICLR 2023Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency
  2. ICLR 2023Representation Learning for Low-rank General-sum Markov Games
  3. ICLR 2023ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor
  4. ICLR 2023Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments
  5. ICLR 2023Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
  6. ICLR 2023Reward Design with Language Models
  7. ICLR 2023Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation
  8. ICLR 2023RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
  9. ICLR 2023ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs
  10. ICLR 2023RPM: Generalizable Multi-Agent Policies for Multi-Agent Reinforcement Learning
  11. ICLR 2023Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL
  12. ICLR 2023Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation
  13. ICLR 2023Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks
  14. ICLR 2023Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
  15. ICLR 2023Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing
  16. ICLR 2023Scaling Laws for a Multi-Agent Reinforcement Learning Model
  17. ICLR 2023Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL
  18. ICLR 2023Simple Emergent Action Representations from Multi-Task Policy Training
  19. ICLR 2023Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective
  20. ICLR 2023SMART: Self-supervised Multi-task pretrAining with contRol Transformers
  21. ICLR 2023Solving Continuous Control via Q-learning
  22. ICLR 2023Spectral Decomposition Representation for Reinforcement Learning
  23. ICLR 2023SpeedyZero: Mastering Atari with Limited Data and Time
  24. ICLR 2023Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning
  25. ICLR 2023Statistical Efficiency of Score Matching: The View from Isoperimetry
  26. ICLR 2023Stay Moral and Explore: Learn to Behave Morally in Text-based Games
  27. ICLR 2023Systematic Rectification of Language Models via Dead-end Analysis
  28. ICLR 2023Task Ambiguity in Humans and Language Models
  29. ICLR 2023TEMPERA: Test-Time Prompt Editing via Reinforcement Learning
  30. ICLR 2023Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning
  31. ICLR 2023The In-Sample Softmax for Offline Reinforcement Learning
  32. ICLR 2023The Power of Regularization in Solving Extensive-Form Games
  33. ICLR 2023The Provable Benefit of Unsupervised Data Sharing for Offline Reinforcement Learning
  34. ICLR 2023The Role of Coverage in Online Reinforcement Learning
  35. ICLR 2023The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry
  36. ICLR 2023Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints
  37. ICLR 2023Towards Effective and Interpretable Human-Agent Collaboration in MOBA Games: A Communication Perspective
  38. ICLR 2023Towards Interpretable Deep Reinforcement Learning with Human-Friendly Prototypes
  39. ICLR 2023Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs
  40. ICLR 2023Transformer-based model for symbolic regression via joint supervised learning
  41. ICLR 2023Transformer-based World Models Are Happy With 100k Interactions
  42. ICLR 2023Transformers are Sample-Efficient World Models
  43. ICLR 2023Truthful Self-Play
  44. ICLR 2023Understanding and Adopting Rational Behavior by Bellman Score Estimation
  45. ICLR 2023User-Interactive Offline Reinforcement Learning
  46. ICLR 2023Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning
  47. ICLR 2023Variational Information Pursuit for Interpretable Predictions
  48. ICLR 2023Variational Latent Branching Model for Off-Policy Evaluation
  49. ICLR 2023VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
  50. ICLR 2023VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查强化学习在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?

AI 会调用的工具:get_topic_stats {"topic": "reinforcement-learning"}

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常见问题

2023–2026 年四大会议一共有多少篇强化学习论文?
共 6,885 篇,按年份分别是 2023 年 1,070 篇、2024 年 1,190 篇、2025 年 1,640 篇、2026 年 2,985 篇。
NeurIPS 2026 有多少篇强化学习论文?
NeurIPS 2026 有 760 篇强化学习论文,上一届是 784 篇。
ICLR 2026 有多少篇强化学习论文?
ICLR 2026 有 911 篇强化学习论文,上一届是 379 篇。
ICML 2026 有多少篇强化学习论文?
ICML 2026 有 1,021 篇强化学习论文,上一届是 405 篇。
CVPR 2026 有多少篇强化学习论文?
CVPR 2026 有 293 篇强化学习论文,上一届是 72 篇。
哪个会议的强化学习论文最多?
NeurIPS,2023–2026 年共 2,494 篇。