A Task Allocation Strategy based on Hungarian Algorithm in RoboCup Rescue Simulation

Abstract

In the multi-agent cooperation of RoboCup Rescue Agent Simulation, as one of the three agents, the agent with the task of clearing roadblocks plays a significant role. The clearing behavior help other agents to work promptly and provide a highly efficient operation to the entire simulation system. However, considering the cost of all agents in a limited time, it is not easy to carry out flexible task allocation, which leads to the current strategy is not perfect, and finally leads to the low efficiency of rescue operations. Therefore, it is necessary to make sure the high efficiency of clearing behavior. In order to maximize the resources of agents, this article puts forward a task allocation strategy based on Hungarian algorithm, which has substantially enhanced the agents’ efficiency through experimental verification at last.