- 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
- (Done)Algorithms for Inverse Reinforcement Learning [v]
- (Done)Apprenticeship Learning via Inverse Reinforcement Learning [v]
- (Done)Maximum Margin Planning [v]
- Maximum Entropy Inverse Reinforcement Learning [v]
- Nonlinear Inverse Reinforcement Learning with Gaussian Processes
- Maximum Entropy Deep Inverse Reinforcement Learning
- Generative Adversarial Imitation Learning
- A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models
- Learning agents for uncertain environments - Russell (1998)
- Apprenticeship Learning via Inverse Reinforcement Learning Supplementary Material - Abbeel & Ng (2004)
- Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods - Neu & Szepesvari (2007)
- Bayesian Inverse Reinforcement Learning (2007)
- Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations(2018 ICML)
- Active Learning for Reward Estimation in Inverse Reinforcement Learning(2009 ECML)
- Multi-Robot Inverse Reinforcement Learning under Occlusion with Interactions(2014 AAMAS)
- Inverse Reinforcement Learning algorithms and features for robot navigation in crowds: An experimental comparison(2014 IROS)
- Teaching Inverse Reinforcement Learners via Features and Demonstrations(2018 NIPS; Luis Haug,Sebastian Tschiatschek,Adish Singla)
- Multi-Agent Generative Adversarial Imitation Learning(2018 NIPS; Jiaming Song,Hongyu Ren,Dorsa Sadigh,Stefano Ermon)
- Lifelong Inverse Reinforcement Learning(2018 NIPS; Jorge A. Mendez, Shashank Shivkumar, and Eric Eaton)
- Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations(2018 ICML; Xingyu Wang, Diego Klabjan)
- Synthesizing Programs for Images using Reinforced Adversarial Learning(2018 ICML; Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals)
- 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 )
- 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)
- Adversarial Imitation via Variational Inverse Reinforcement Learning(2019 ICLR; Ahmed H. Qureshi, Byron Boots, Michael C. Yip)
- A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress link
- Inverse reinforcement learning control for trajectory tracking of a multirotor UAV(2017 International Journal of Control, Automation and Systems)
- Inverse reinforcement learning for video games(2018 NIPS workshop; Aaron Tucker, Adam Gleave, Stuart Russell)
- Inverse Reinforcement Learning via Deep Gaussian Process(Ming Jin, Andreas Damianou, Pieter Abbeel, Costas Spanos)
- Learning Robust Rewards with Adversarial Inverse Reinforcement Learning(ICLR 2018; Justin Fu, Katie Luo, Sergey Levine)
- MaxEnt IRL with neural net reward function, known dynamics(Wulfmeier et al)
- Toward Diverse Text Generation with Inverse Reinforcement Learning(IJCAI 2018; Zhan Shi, Xinchi Chen, Xipeng Qiu, Xuanjing Huang)
- (Done)Neural inverse reinforcement learning in autonomous navigation(RSA 2016)
- Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks(NIPS workshop 2016; )
- Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization(ICML 2016; Chelsea Finn, Sergey Levine, Pieter Abbeel)