mlsanityData to 7 Oct 2026

Inverse reinforcement learning

321 papers1 this weekHigh confidence in this grouping: the papers form one clear topicHigh confidence in this grouping: the papers form one clear topic · About

Keywords: reward, inverse, irl, inverse reinforcement, reinforcement

Key facts. Inverse reinforcement learning: 321 papers on arXiv since 2018 (data through 7 Oct 2026). 40 of its 321 mapped papers (12%) cite “A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress” (2018, arXiv 1806.06877). 22 of its 321 mapped papers (7%) cite “Identifiability in inverse reinforcement learning” (2021, arXiv 2106.03498). 4 new papers 17 Sep–7 Oct.

What’s new

17 Sep – 7 Oct 2026

  1. This week · 1
  2. Learning Unknown Constraints without Unsafe Data via Optimality and Counterfactual Regularization
  3. Earlier · 3
  4. Scalable Multi-Task Inverse Reinforcement Learning
  5. Loop-Free Inverse Reinforcement Learning via Sequential Value Recovery with Q-Score Matching
  6. PHIRL: Aligning Learned Rewards with Task Progress for Inverse Reinforcement Learning

Foundations

Most cited by papers here

  1. A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress2018cited by 40 here
  2. Identifiability in inverse reinforcement learning2021cited by 22 here
  3. Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations2019cited by 20 here
  4. f-IRL: Inverse Reinforcement Learning via State Marginal Matching2020cited by 20 here
  5. Scalable Bayesian Inverse Reinforcement Learning2021cited by 19 here

Lineage

The papers this direction builds on, oldest first.

Each paper on the line cites the one before.

  1. 2018Generative Adversarial Imitation from Observationcited by 10 here
  2. 2018Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learningcited by 22 here
  3. 2019SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewardscited by 25 here
  4. 2020f-IRL: Inverse Reinforcement Learning via State Marginal Matchingcited by 20 here
  5. 2022Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guaranteescited by 18 here
19 more it builds on, not in this chain
  1. 2018Behavioral Cloning from Observationcited by 14 here
  2. 2018Learning a Prior over Intent via Meta-Inverse Reinforcement Learningcited by 12 here
  3. 2018A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progresscited by 40 here
  4. 2018Adversarial Imitation via Variational Inverse Reinforcement Learningcited by 14 here
  5. 2018An Algorithmic Perspective on Imitation Learningcited by 21 here
  6. 2019Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observationscited by 20 here
  7. 2019Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrationscited by 10 here
  8. 2019Multi-Agent Adversarial Inverse Reinforcement Learningcited by 17 here
  9. 2019Meta-Inverse Reinforcement Learning with Probabilistic Context Variablescited by 16 here
  10. 2019A Divergence Minimization Perspective on Imitation Learning Methodscited by 15 here
  11. 2019Imitation Learning via Off-Policy Distribution Matchingcited by 19 here
  12. 2020D4RL: Datasets for Deep Data-Driven Reinforcement Learningcited by 17 here
  13. 2020Conservative Q-Learning for Offline Reinforcement Learningcited by 11 here
  14. 2020Robust Inverse Reinforcement Learning under Transition Dynamics Mismatchcited by 10 here
  15. 2021Scalable Bayesian Inverse Reinforcement Learningcited by 19 here
  16. 2021Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gapcited by 12 here
  17. 2021Identifiability in inverse reinforcement learningcited by 22 here
  18. 2021IQ-Learn: Inverse soft-Q Learning for Imitationcited by 36 here
  19. 2022Active Exploration for Inverse Reinforcement Learningcited by 11 here

The 24 most cited of 402.

Browse

30 of 321, ranked 6–35

  1. 6Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees202218
  2. 7Multi-Agent Adversarial Inverse Reinforcement Learning201917
  3. 8Meta-Inverse Reinforcement Learning with Probabilistic Context Variables201916
  4. 9Adversarial Imitation via Variational Inverse Reinforcement Learning201814
  5. 10Learning a Prior over Intent via Meta-Inverse Reinforcement Learning201812
  6. 11Active Exploration for Inverse Reinforcement Learning202211
  7. 12Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning202210
  8. 13Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch202010
  9. 14Multi-task Maximum Entropy Inverse Reinforcement Learning20189
  10. 15Inverse reinforcement learning for video games20189
All 30
  1. 16When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning20238
  2. 17Towards Theoretical Understanding of Inverse Reinforcement Learning20238
  3. 18Multi-agent Inverse Reinforcement Learning for Certain General-sum Stochastic Games20188
  4. 19Identifiability and Generalizability in Constrained Inverse Reinforcement Learning20237
  5. 20OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching20217
  6. 21Regularized Inverse Reinforcement Learning20207
  7. 22Inverse Reinforcement Learning without Reinforcement Learning20236
  8. 23Receding Horizon Inverse Reinforcement Learning20226
  9. 24Risk-Aware Active Inverse Reinforcement Learning20196
  10. 25Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations20186
  11. 26Walking the Values in Bayesian Inverse Reinforcement Learning20245
  12. 27Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees20215
  13. 28Off-Policy Adversarial Inverse Reinforcement Learning20205
  14. 29Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms20205
  15. 30On the Correctness and Sample Complexity of Inverse Reinforcement Learning20195
  16. 31Identifying Cognitive Radars -- Inverse Reinforcement Learning using Revealed Preferences20195
  17. 32Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications20185
  18. 33A Framework and Method for Online Inverse Reinforcement Learning20185
  19. 34CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning20234
  20. 35A Primer on Maximum Causal Entropy Inverse Reinforcement Learning20224