Goal-Oriented Multi-Agent Semantic Networking: Unifying Intents, Semantics, and Intelligence

2025-11-30

AI Summary

Existing network architectures fully decouple applications from the underlying infrastructure, rendering them incapable of perceiving high-level task intent and thus hindering dynamic adaptation to intelligent service requirements. To address this, this paper proposes GoAgentNet—a goal-driven, multi-agent semantic networking architecture aligned with the 6G objective-oriented paradigm. GoAgentNet is the first framework to unify semantic representation, intent modeling, and intelligent decision-making, enabling cross-layer coordination and global objective-driven resource orchestration. It integrates semantic computing, cross-layer semantic networking, multi-agent perception–control loops, and AI-native communication to establish an end-edge-cloud collaborative intelligent network. Evaluated in a robotic fault detection and recovery scenario, GoAgentNet achieves a 99% improvement in energy efficiency and a 72% increase in task success rate over conventional architectures, significantly enhancing the scalability and sustainability of 6G systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Agent/AI Theories and Architectures
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search

Abstract

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.

Problem

• Addresses limitations of current networks in supporting 6G goal-oriented services
• Introduces a multi-agent architecture to unify application and network collaboration
• Enhances energy efficiency and task success for intelligent 6G systems

Innovation

• Multi-agent collaboration abstracts functions into agents
• Semantic computation orchestrates sensing, networking, and control
• Cross-layer semantic networking unifies application goals