文献类型：期刊文献

英文题名：Integrated adaptive communication in multi-agent systems: Dynamic topology, frequency, and content optimization for efficient collaboration

作者：Wang, Jianrui[1];Li, Yi[1];Hong, Yitian[1];Tang, Yang[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Shanghai 200237, Peoples R China

年份：2025

卷号：617

外文期刊名：NEUROCOMPUTING

收录：;EI(收录号：20245017498071);WOS:【SCI-EXPANDED(收录号:WOS:001374560600001)】；

基金：This work was supported by the Natural Science Foundation of China 62233005, U2441245, the Fundamental Research Funds for the Central Universities 222202417006, and the Programme of Introducing Talents of Discipline to Universities (the 111 Project) B17017.

语种：英文

外文关键词：Multi-agent systems; Integrated adaptive communication network; MAPPO; Graph attention mechanism

摘要：In multi-agent systems (MAS), effective communication is essential for coordination and achieving common goals, especially in complex environments. However, existing communication methods face significant challenges, such as high resource consumption and limited adaptability to dynamic environments. To address these, we propose the integrated adaptive communication network (IACN) built on multi-agent proximal policy optimization (MAPPO), which enhances communication efficiency and adaptability in MAS. IACN dynamically adjusts communication topology using a learnable graph and optimizes content based on task relevance. Additionally, it incorporates an adaptive frequency adjustment mechanism to balance communication demands based on task urgency and environmental changes. Experiments in multi-agent particle environments demonstrate that IACN significantly outperforms existing methods in terms of overall performance, coordination effectiveness, and adaptability.