Communication could potentially be an effective way for multi-agent
cooperation. However, information sharing among all agents or in predefined
communication architectures that existing methods adopt can be probl
本文提出了 Individualized Controlled Continuous Communication Model (IC3Net)，在多智能体协作、半协作与竞争环境下，通过门控机制控制持续传输，并使用个性化奖励来提高性能和可扩展性，修正学分分配问题。实验结果证实，IC3Net 网络比基准网络在不同场景下具有更好的训练效率和收敛率，智能体基于场景和可盈利性学会如何传输信息。