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1. Learning Decision Making Strategies of Non-experts: A NEXT-GAIL Model for Taxi Drivers

   https://doi.org/10.1145/3474717.3483924  

   Pan, Menghai ; Zhang, Xin ; Li, Yanhua ; Zhou, Xun ; Luo, Jun ( November 2021 , SIGSPATIAL '21: Proceedings of the 29th International Conference on Advances in Geographic Information Systems)
2. f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning

   Zhang, Xin ; Li, Yanhua ; Zhang, Ziming ; Zhang, Zhi-Li ( January 2020 , Advances in neural information processing systems)

   null (Ed.)

   Imitation learning (IL) aims to learn a policy from expert demonstrations that minimizes the discrepancy between the learner and expert behaviors. Various imitation learning algorithms have been proposed with different pre-determined divergences to quantify the discrepancy. This naturally gives rise to the following question: Given a set of expert demonstrations, which divergence can recover the expert policy more accurately with higher data efficiency? In this work, we propose f-GAIL – a new generative adversarial imitation learning model – that automatically learns a discrepancy measure from the f-divergence family as well as a policy capable of producing expert-like behaviors. Compared with IL baselines with various predefined divergence measures, f-GAIL learns better policies with higher data efficiency in six physics-based control tasks. 

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3. f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning

   Zhang, Xin ; Li, Yanhua ; Zhang, Ziming ; Zhang, Zhi-Li ( December 2020 , Advances in neural information processing systems)

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4. f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning

   Zhang, Xin ; Li, Yanhua ; Zhang, Ziming ; Zhang, Zhi-Li ( January 2020 , Advances in neural information processing systems)

   null (Ed.)
5. f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning

   Zhang, Xin ; Li, Yanhua ; Zhang, Ziming ; Zhang, Zhi-Li. ( December 2020 , Advances in neural information processing systems)

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