ndroi / Inverse-Reinforcemant-Learning-Paper

Inverse Reinforcement Learning (IRL) Papers

Tutorial/Blog

• Thinkingwires
• 2018CVPR IRL Tutorial Video
• Max's Blog
• Sergey Levine
• CSDN-漫谈逆向强化学习
• Toward Data Science
• Udacity
• 知乎CS 294: Deep Reinforcement Learning：IRL
• Coursera

Code/Repo

• Inverse-Reinforcement-Learning

Paper

1. (Done)Algorithms for Inverse Reinforcement Learning [v]
2. (Done)Apprenticeship Learning via Inverse Reinforcement Learning [v]
3. (Done)Maximum Margin Planning [v]
4. Maximum Entropy Inverse Reinforcement Learning [v]
5. Nonlinear Inverse Reinforcement Learning with Gaussian Processes
6. Maximum Entropy Deep Inverse Reinforcement Learning
7. Generative Adversarial Imitation Learning
8. A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models
9. Learning agents for uncertain environments - Russell (1998)
10. Apprenticeship Learning via Inverse Reinforcement Learning Supplementary Material - Abbeel & Ng (2004)
11. Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods - Neu & Szepesvari (2007)
12. Bayesian Inverse Reinforcement Learning (2007)
13. Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations(2018 ICML)
14. Active Learning for Reward Estimation in Inverse Reinforcement Learning(2009 ECML)
15. Multi-Robot Inverse Reinforcement Learning under Occlusion with Interactions(2014 AAMAS)
16. Inverse Reinforcement Learning algorithms and features for robot navigation in crowds: An experimental comparison(2014 IROS)
17. Teaching Inverse Reinforcement Learners via Features and Demonstrations(2018 NIPS; Luis Haug,Sebastian Tschiatschek,Adish Singla)
18. Multi-Agent Generative Adversarial Imitation Learning(2018 NIPS; Jiaming Song,Hongyu Ren,Dorsa Sadigh,Stefano Ermon)
19. Lifelong Inverse Reinforcement Learning(2018 NIPS; Jorge A. Mendez, Shashank Shivkumar, and Eric Eaton)
20. Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations(2018 ICML; Xingyu Wang, Diego Klabjan)
21. Synthesizing Programs for Images using Reinforced Adversarial Learning(2018 ICML; Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals)
22. An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning(2018 ICML; Dhruv Malik, Malayandi Palaniappan, Jaime Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca Dragan )
23. Integrating kinematics and environment context into deep inverse reinforcement learning for predicting off-road vehicle trajectories(2018 CoRL; Yanfu Zhang, Wenshan Wang, Rogerio Bonatti, Daniel Maturana, Sebastian Scherer)
24. Adversarial Imitation via Variational Inverse Reinforcement Learning(2019 ICLR; Ahmed H. Qureshi, Byron Boots, Michael C. Yip)
25. A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress link
26. Inverse reinforcement learning control for trajectory tracking of a multirotor UAV(2017 International Journal of Control, Automation and Systems)
27. Inverse reinforcement learning for video games(2018 NIPS workshop; Aaron Tucker, Adam Gleave, Stuart Russell)
28. Inverse Reinforcement Learning via Deep Gaussian Process(Ming Jin, Andreas Damianou, Pieter Abbeel, Costas Spanos)
29. Learning Robust Rewards with Adversarial Inverse Reinforcement Learning(ICLR 2018; Justin Fu, Katie Luo, Sergey Levine)
30. MaxEnt IRL with neural net reward function, known dynamics(Wulfmeier et al)
31. Toward Diverse Text Generation with Inverse Reinforcement Learning(IJCAI 2018; Zhan Shi, Xinchi Chen, Xipeng Qiu, Xuanjing Huang)
32. (Done)Neural inverse reinforcement learning in autonomous navigation(RSA 2016)
    • Slide
33. Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks(NIPS workshop 2016; )
34. Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization(ICML 2016; Chelsea Finn, Sergey Levine, Pieter Abbeel)