This paper addresses team formation in the RoboCup Rescue centered on task allocation. We follow a previous approach that is based on so-called extreme teams, which have four key characteristics: agents act in domains that are dynamic; agents may perform multiple tasks; agents have overlapping functionality regarding the execution of each task but differing levels of capability; and some tasks may depict constraints such as simultaneous execution. So far these four characteristics have not been fully tested in domains such as the RoboCup Rescue. We use a swarm intelligence based approach, address all characteristics, and compare it to other two GAP-based algorithms. Experiments where computational effort, communication load, and the score obtained in the RoboCup Rescue aremeasured, show that our approach outperforms the others.
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dos Santos, F., Bazzan, A.L.C. Towards efficient multiagent task allocation in the RoboCup Rescue: a biologically-inspired approach. Auton Agent Multi-Agent Syst 22, 465–486 (2011). https://doi.org/10.1007/s10458-010-9136-3
- Optimisation in multiagent systems
- Task allocation
- Robocup Rescue
- Swarm intelligence