Deep Reinforcement Learning based Multi-attribute Auction Model for Resource Allocation in Vehicular AIGC Services-Reference-Cited by-同舟云学术

Deep Reinforcement Learning based Multi-attribute Auction Model for Resource Allocation in Vehicular AIGC Services

Published:2024-05-10 Issue: Volume:1 Page:36-42
ISSN:
Container-title:Proceedings of the 2024 International Conference on Generative Artificial Intelligence and Information Security
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Author:

Tong Yongju¹^ORCID,Kang Jiawen¹^ORCID,Chen Junlong¹^ORCID,Xu Minrui²^ORCID,Yang Helin³^ORCID,Xu Minghui⁴^ORCID,Xie Renchao⁵^ORCID,Xiong Zehui⁶^ORCID

Affiliation:

1. Guangdong University of Technology, China

2. Nanyang Technological University, Singapore

3. Xiamen University, China

4. Shandong University, China

5. Beijing University of Posts and Telecommunications, China

6. Singapore University of Technology and Design, Singapore

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3665348.3665356

Reference15 articles.

1. Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach

2. Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services

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4. Diffusion-based reinforcement learning for edge-enabled ai-generated content services;Du Hongyang;IEEE Transactions on Mobile Computing, pages,2024

5. Minrui Xu, Dusit Niyato, Hongliang Zhang, Jiawen Kang, Zehui Xiong, Shiwen Mao, and Zhu Han. Cached model-as-a-resource: Provisioning large language model agents for edge intelligence in space-air-ground integrated networks. arXiv preprint arXiv:2403.05826, 2024.