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This study addresses these challenges by focusing on the joint optimization of communication, computing, and caching resources in satellite edge computing to support mobile multimedia applications. A mixed-integer nonlinear programming (MINLP) problem is formulated with the objective of minimizing the total delay experienced by mobile users, subject to multidimensional resource capacity constraints, which are NP-hard and computationally intractable to solve in polynomial time. To address this complexity, we propose a multi-agent federated reinforcement learning (MAFRL) approach as an efficient solution. In this framework, each satellite operates as an autonomous learning agent equipped with an actor-critic network structure. The proposed MAFRL method demonstrates superior performance, achieving lower delays compared to all baseline approaches. It effectively optimizes delay-sensitive mobile multimedia communications by minimizing total delay and improving task-offloading ratios. To the best of the authors\u2019 knowledge, this study is the first to introduce an MAFRL-based approach for resource allocation in satellite edge computing, marking a significant contribution to the field.<\/jats:p>","DOI":"10.1145\/3715146","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T08:16:02Z","timestamp":1738570562000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Satellite Edge Computing for Mobile Multimedia Communications: A Multi-agent Federated Reinforcement Learning Approach"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0953-5047","authenticated-orcid":false,"given":"Weiwei","family":"Jiang","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3869-4592","authenticated-orcid":false,"given":"Yafeng","family":"Zhan","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7015-5524","authenticated-orcid":false,"given":"Xin","family":"Fang","sequence":"additional","affiliation":[{"name":"State Grid Jiangsu Electric Power Co., Ltd. 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