PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization-Reference-Cited by-同舟云学术

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PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization

Published:2024-08-24 Issue: Volume:11 Page:6148-6157
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Ye Yuyang¹^ORCID,Tang Lu-An²^ORCID,Wang Haoyu²^ORCID,Yu Runlong³^ORCID,Yu Wenchao²^ORCID,He Erhu²^ORCID,Chen Haifeng²^ORCID,Xiong Hui⁴^ORCID

Affiliation:

1. Department of Management Science and Information Systems, Rutgers Business School, Rutgers University, Newark, NJ, USA

2. Department of Data Science and System Security, NEC Laboratories, Princeton, NJ, USA

3. Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, USA

4. Thrust of Artificial Intelligence, Hong Kong University of Science and Technology (Guangzhou) & Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Guangzhou, China

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671611

Reference57 articles.

1. Apprenticeship learning via inverse reinforcement learning

2. Reinforcement Learning with a Gaussian mixture model

3. Modeling Human Driving Behavior Through Generative Adversarial Imitation Learning

4. Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl. 2020. Learning by cheating. In Conference on Robot Learning. PMLR, 66--75.

5. TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning

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