6G services are evolving toward goal-oriented and AI-native communication, which are expected to deliver transformative societal benefits across various industries and promote energy sustainability. Yet today's networking architectures, built on complete decoupling of the applications and the network, cannot expose or exploit high-level goals, limiting their ability to adapt intelligently to service needs. This work introduces Goal-Oriented Multi-Agent Semantic Networking (GoAgentNet), a new architecture that elevates communication from data exchange to goal fulfilment. GoAgentNet enables applications and the network to collaborate by abstracting their functions into multiple collaborative agents, and jointly orchestrates multi-agent sensing, networking, computation, and control through semantic computation and cross-layer semantic networking, allowing the entire architecture to pursue unified application goals. We first outline the limitations of legacy network designs in supporting 6G services, based on which we highlight key enablers of our GoAgentNet design. Then, through three representative 6G usage scenarios, we demonstrate how GoAgentNet can unlock more efficient and intelligent services. We further identify unique challenges faced by GoAgentNet deployment and corresponding potential solutions. A case study on robotic fault detection and recovery shows that our GoAgentNet architecture improves energy efficiency by up to 99% and increases the task success rate by up to 72%, compared with the existing networking architectures without GoAgentNet, which underscores its potential to support scalable and sustainable 6G systems.

翻译：6G服务正朝着面向目标与AI原生的通信方向演进，有望在多个行业带来变革性社会效益并促进能源可持续性。然而，当今建立在应用与网络完全解耦基础上的组网架构，无法暴露或利用高层目标，限制了其根据服务需求进行智能适配的能力。本工作提出面向目标的多智能体语义组网（GoAgentNet），这是一种将通信从数据交换提升至目标实现的新型架构。GoAgentNet通过将应用与网络的功能抽象为多个协作智能体，并利用语义计算与跨层语义组网联合编排多智能体感知、组网、计算与控制，使整个架构能够追求统一的应用目标。我们首先概述传统网络设计在支撑6G服务方面的局限性，并据此突出GoAgentNet设计的关键使能技术。随后，通过三个典型6G使用场景，我们展示了GoAgentNet如何解锁更高效、更智能的服务。我们进一步识别GoAgentNet部署面临的独特挑战及相应的潜在解决方案。针对机器人故障检测与恢复的案例研究表明，与未采用GoAgentNet的现有组网架构相比，我们的GoAgentNet架构可将能效提升高达99%，任务成功率提升高达72%，凸显了其支撑可扩展且可持续的6G系统的潜力。