Multi-agent Planning for the RoboCup Rescue Simulation - Applying Clustering into Task Allocation and Coordination

The RoboCup Rescue Simulation system provides a rich environment for developing novel techniques for multi-agent systems. The simulation provides a city map modeled as buildings and roads with civilians amongst them. A disaster scenario is simulated causing buildings to catch fire, roads to get blocked, and civilians to get injured and/or buried. The main goal is to use the available emergency services (rescue agents) to extinguish the fires, clear the roads, and rescue the civilians. This paper describes a new multi-agent planning approach applied to the RoboCup Rescue problem. Task allocation coordination is done through clustering the map into several overlapping maps each with a different group of agents assigned to it. Our results show that by applying this approach to the RoboCup Rescue Simulation we did compete with the top teams in the 2011 RoboCup Rescue Agent Simulation Competition and ranked 3rd in our first participation in the competition.