Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm

This paper proposes a multi-agent technique for modeling and simulating multiple objects and multiple sensor tracking for drones. The goal is to achieve efficient resource allocation based on different preset cost functions that take into account several local and global attributes. The target dynamics, the sensor selection, and the measurements are simulated by way of an agent-based modeling framework called MESA. The results show an optimum resource allocation with an information-based cost function that is optimized by an Auction Algorithm.