Task Allocation

Task allocation, the process of assigning tasks to agents (robots, humans, or both), aims to optimize efficiency, resource utilization, and overall system performance. Current research heavily focuses on dynamic environments and heterogeneous teams, employing diverse approaches including reinforcement learning (particularly hierarchical RL), swarm algorithms (like those inspired by Levy walks or pheromone-based methods), and optimization techniques (e.g., linear programming, branch and bound). These advancements are crucial for improving the coordination of multi-agent systems in various applications, such as robotics, logistics, and disaster response, by enabling more robust and adaptable task assignments.