arXiv Artificial Intelligence

General Collaborative Intelligence: Architecting Cognition for Resilient Multi-Agent Ecosystems

General Collaborative Intelligence: Architecting Cognition for Resilient Multi-Agent Ecosystems

Quick summary

arXiv:2609.22967v1 Announce Type: cross Abstract: Multi-agent unmanned systems are moving from isolated, ego-centric sensing toward collaborative intelligence, in which distributed agents exchange compact features to overcome a local observation trap that no single agent can escape: occlusions, finite sensor range, and environmental degradation. The field has matured across architectural, communication, embodied, resilience, and trust dimensions, yet existing surveys examine these dimensions in isolation and rarely expose their dependencies. This review offers a unified synthesis through two c

Key takeaways

  • arXiv:2609.22967v1 Announce Type: cross Abstract: Multi-agent unmanned systems are moving from isolated, ego-centric sensing toward collaborative intelligence, in which distributed agents exchange compact features to overcome a local observation trap that no single agent can escape: occlusions, finite sensor range, and environmental degradation.
  • The field has matured across architectural, communication, embodied, resilience, and trust dimensions, yet existing surveys examine these dimensions in isolation and rarely expose their dependencies.
  • This review offers a unified synthesis through two c

Why it matters

The importance of “General Collaborative Intelligence: Architecting Cognition for Resilient Multi-Agent Ecosystems” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗