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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract)

February 1, 2023

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Authors

Jiacheng Zhu

Soochow University


Jiahao Lin

Soochow University


Meng Wang

Fuxi AI Lab


Yingfeng Chen

Fuxi AI Lab


Changjie Fan

Fuxi AI Lab


Chong Jiang

Soochow University


Zongzhang Zhang

Nanjing University


DOI:

10.1609/aaai.v34i10.7271


Abstract:

Imitation learning provides a family of promising methods that learn policies from expert demonstrations directly. As a model-free and on-line imitation learning method, generative adversarial imitation learning (GAIL) generalizes well to unseen situations and can handle complex problems. In this paper, we propose a novel variant of GAIL called GAIL from failed experiences (GAILFE). GAILFE allows an agent to utilize failed experiences in the training process. Moreover, a constrained optimization objective is formalized in GAILFE to balance learning from given demonstrations and from self-generated failed experiences. Empirically, compared with GAIL, GAILFE can improve sample efficiency and learning speed over different tasks.

Topics: AAAI

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HOW TO CITE:

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract) Proceedings of the AAAI Conference on Artificial Intelligence (2020) 13997-13998.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract) AAAI 2020, 13997-13998.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang (2020). Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 13997-13998.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang. Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.13997-13998.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang. 2020. Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract). "Proceedings of the AAAI Conference on Artificial Intelligence". 13997-13998.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang. (2020) "Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract)", Proceedings of the AAAI Conference on Artificial Intelligence, p.13997-13998

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang, "Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract)", AAAI, p.13997-13998, 2020.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang. "Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.13997-13998.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang. "Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 13997-13998.

Jiacheng Zhu||Jiahao Lin||Meng Wang||Yingfeng Chen||Changjie Fan||Chong Jiang||Zongzhang Zhang. Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract). AAAI[Internet]. 2020[cited 2023]; 13997-13998.


ISSN: 2374-3468


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