LLM-Based Agentic Negotiation for 6G: Addressing Uncertainty Neglect and Tail-Event Risk

Documenti analoghi

• A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks
  di: Chergui, Hatim, et al.
  Pubblicazione: (2025)
• Joint Explainability and Sensitivity-Aware Federated Deep Learning for Transparent 6G RAN Slicing
  di: Roy, Swastika, et al.
  Pubblicazione: (2023)
• Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
  di: Rezazadeh, Farhad, et al.
  Pubblicazione: (2025)
• LiQSS: Post-Transformer Linear Quantum-Inspired State-Space Tensor Networks for Real-Time 6G
  di: Rezazadeh, Farhad, et al.
  Pubblicazione: (2026)
• Agentic World Modeling for 6G: Near-Real-Time Generative State-Space Reasoning
  di: Rezazadeh, Farhad, et al.
  Pubblicazione: (2025)