Awesome Inverse Reinforcement Learning

An awesome list of papers (eventually summaries too), code, videos and tutorials related to Inverse Reinforcement Learning.

Papers

Algorithms for Inverse Reinforcement Learning - Andrew Ng & Stuart Russell (2000)
Apprenticeship Learning via Inverse Reinforcement Learning - Pieter Abbeel & Andrew Ng (2004)
Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods - Neu & Szepesvari (2007)
Modeling Interaction via the Principle of Maximum Causal Entropy - Ziebart et. al. (2008)
Modeling Purposeful Adaptive Behavior with the Principle of Maximum Causal Entropy - Brian Ziebart’s PhD Thesis (2010)
Bayesian Inverse Reinforcement Learning - Deepak Ramachandran & Eyal Amir (2006)
Relative Entropy Inverse Reinforcement Learning - Boularias et. al. (2011)
Maximum Entropy Deep Inverse Reinforcement Learning - Wulfmeier et al. (2016)
Hierarchical Bayesian Inverse Reinforcement Learning. Kim et al. (2012)
Guided Cost Learning. Finn et al. (2016)
Generative Adversarial Imitation Learning - Jonathan Ho and Stefano Ermon (2016)
Occam’s razor is insufficient to infer the preferences of irrational agents - Stuart Armstrong and Sören Mindermann (2018)
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning - Daniel S. Brown et. al. (2019)
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference - Rohin Shah et. al. (2019)

irl_rocks/IRL_survey.pdf
A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress - Saurabh Arora and Prashant Doshi

Inverse Reinforcement Learning Tutorial | part I | thinking wires - Johannes Heidecke
Learning from humans: what is inverse reinforcement learning? - Jordan Alexander