Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Multidimensional binary search trees used for associative searching
Communications of the ACM
Improving Regressors using Boosting Techniques
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Towards the integration of real-time real-world data in urban search and rescue simulation
MobileResponse'07 Proceedings of the 1st international conference on Mobile information technology for emergency response
Task allocation learning in a multiagent environment: Application to the RoboCupRescue simulation
Multiagent and Grid Systems
Agent-based simulation for large-scale emergency response: A survey of usage and implementation
ACM Computing Surveys (CSUR)
RMASBench: benchmarking dynamic multi-agent coordination in urban search and rescue
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Weighted synergy graphs for effective team formation with heterogeneous ad hoc agents
Artificial Intelligence
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RoboCupRescue Simulation is a large-scale multi-agent simulation of urban disasters where, in order to save lives and minimize damage, rescue teams must effectively cooperate despite sensing and communication limitations. This paper presents the comprehensive search and rescue approach of the ResQ Freiburg team, the winner in the RoboCupRescue Simulation league at RoboCup 2004. Specific contributions include the predictions of travel costs and civilian life-time, the efficient coordination of an active disaster space exploration, as well as an any-time rescue sequence optimization based on a genetic algorithm. We compare the performances of our team and others in terms of their capability of extinguishing fires, freeing roads from debris, disaster space exploration, and civilian rescue. The evaluation is carried out with information extracted from simulation log files gathered during RoboCup 2004. Our results clearly explain the success of our team, and also confirm the scientific approaches proposed in this paper.