The article reviews significant advances in networked signal and information processing, which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments of distributed agents. As these interacting agents cooperate, new collective behaviors emerge from local decisions and actions. Moreover, and significantly, theory and applications show that networked agents, through cooperation and sharing, are able to match the performance of cloud or federated solutions, while offering the potential for improved privacy, increasing resilience, and saving resources.

翻译：本文综述了网络化信号与信息处理领域的重大进展，这些进展在过去25年中使决策与推理、优化、控制及学习能力得以扩展至日益普及的分布式智能体环境。当这些相互作用的智能体进行协作时，新涌现的集体行为源于局部的决策与行动。尤为重要的是，理论与应用均表明，网络化智能体通过合作与共享，能够达到与云端或联邦解决方案相当的性能，同时具备增强隐私保护、提升抗毁性及节约资源的潜力。