@conference {43,
	title = {RMASBench: Benchmarking Dynamic Multi-Agent Coordination in Urban Search and Rescue},
	booktitle = {Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013)},
	year = {2013},
	abstract = {We propose RMASBench, a new benchmarking tool based on the RoboCup Rescue Agent simulation system, to easily compare coordination approaches in a dynamic rescue scenario. In particular, we offer simple interfaces to plug-in coordination algorithms without the need for implementing and tuning low-level agents behaviors. Moreover, we add to the realism of the simulation by providing a large scale crowd simulator, which exploits GPUs parallel architecture, to simulate the behavior of thousands of agents in real time. Finally, we focus on a specific coordination problem where fire fighters must combat fires and prevent them from spreading across the city. We formalize this problem as a Distributed Constraint Optimization Problem and we compare two state-of-the art solution techniques: DSA and MaxSum. We perform an extensive empirical evaluation of such techniques considering several standard measures for performance (e.g. damages to buildings) and coordination overhead (e.g., message exchanged and non concurrent constraint checks). Our results provide interesting insights on limitations and benefits of DSA and MaxSum in our rescue scenario and demonstrate that RMASBench offers powerful tools to compare coordination algorithms in a dynamic environment.},
	keywords = {agent coordination, agent simulation, DCOP, performance metrics},
	isbn = {978-1-4503-1993-5},
	url = {http://dl.acm.org/citation.cfm?id=2484920.2485139},
	author = {A. Kleiner and A. Farinelli and S. Ramchurn and B. Shi and F. Maffioletti and R. Reffato}
}
@article {40,
	title = {RoboCup Rescue Robot and Simulation Leagues},
	journal = {AI Magazine},
	volume = {34},
	year = {2013},
	pages = {78{\textendash}87},
	abstract = {The RoboCup Rescue Robot and Simulation competitions have been held since 2000. The experience gained during these competitions has increased the maturity level of the field, which allowed deploying robots after real disasters (e.g. Fukushima Daiichi nuclear disaster). This article provides an overview of these competitions and highlights the state of the art and the lessons learned.},
	author = {H. L. Akin and N. Ito and A. Jacoff and A. Kleiner and J. Pellenz and A. Visser}
}
