ADeCoS 2026

Future softwarized networks are evolving toward highly decentralized and multi-domain operation. While Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and cloud-native platforms enabled programmability, centralized orchestration is increasingly limited in terms of scalability, responsiveness, resilience, and trust.

ADeCoS 2026 aims to shape the next generation of AI-native and decentralized network control, where agentic AI systems autonomously coordinate decisions across domains, stakeholders, and layers of the network. These systems go beyond traditional automation by incorporating goal-driven behavior, adaptive communication, and context-aware decision-making.

The workshop focuses on fundamental and practical challenges in enabling such systems, including multi-agent coordination, intent-to-action translation, learning and planning under uncertainty, and policy-aware control with built-in safety and verification mechanisms.

Despite recent advances in AI-driven network management, scalable and trustworthy decentralized coordination across domains remains largely unresolved. ADeCoS 2026 aims to address this gap by bringing together researchers and practitioners from networking, distributed systems, and AI.

The workshop emphasizes realistic deployments, experimental validation, and reproducibility, fostering new directions toward trustworthy, scalable, and autonomous network infrastructures.