Project 1.4: Multi-Agent Task Allocation (MATA) - (Concept Only)

We are investigating the Coordination Bottleneck in large-scale infrastructure projects. Without a robust theoretical framework for task distribution, robotic fleets risk "Deadlocks"—where interdependent tasks lead to idle agents or resource conflicts.

This study matters because it explores the Scalability Layer. We are theorizing how a system could coordinate dozens of specialized agents in parallel without a central point of failure, shifting the burden of management from human oversight to autonomous organizational logic.

The MATA framework is envisioned as the Organizational Intelligence of the STC. We are currently mapping the hypothetical requirements for this "Project Manager" role:

• Capability Mapping: Identifying how to abstract diverse agent hardware (Project 3.5) into a universal "Skill Matrix."
• Logic Sequences: Researching how high-level mission goals can be decomposed into individual agent priority queues.
• Fault Tolerance: Theorizing how telemetry data could trigger a real-time "Redistribution Protocol" if an agent suddenly goes offline.

The methodology focuses on evaluating various Distributed Resilience models:

• Market-Based Coordination: Investigating decentralized "Auction" models where agents would hypothetically bid on tasks based on proximity and energy reserves.
• Dynamic Recalculation: Researching reactive logic layers that can identify the "Critical Path" of a construction stream amidst environmental uncertainty.
• Heterogeneous Task Mapping: Defining the theoretical constraints that ensure specialized tasks (e.g., high-torque lifting) are only assigned to agents with the necessary physical profiles.

This project is in the planning phase. No active codebase exists.

Current Focus: NA

• To be confirmed.