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The CoDA Project specializes in smart coordination of collaborative agent teams, including autonomous underwater vehicles and various robotic systems. Specifically, CoDA targets open multiagent systems (MAS) where agents dynamically join or leave during operation. Consider an autonomous oceanographic monitoring network (AOSN) tracking climate shifts - some underwater drones may fail or get reassigned, while new units periodically join the fleet.
Such systems must effectively organize their resources to fulfill objectives and adapt to changing team compositions or mission requirements.
Dual-layer structure
CoDA innovates by employing two organizational layers to optimize both adaptability and performance. Upon deployment, the system's smarter agents communicate to assess available resources and strategize mission execution. This flexible but less efficient meta-level organization (MLO) designs a streamlined task-level organization (TLO) for operational efficiency. When circumstances shift, the TLO either self-adjusts or reactivates the MLO to create an updated structure.
The initiative comprises three key components: autonomous coordination protocols for system management, a constraint-based heuristic search algorithm for job allocation, and a versatile simulation platform for comprehensive testing.
While focused on marine research applications, it's crucial to recognize that