Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
A Combinatorial Auction for Collaborative Planning
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
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Autonomous Agents and Multi-Agent Systems
Allocating tasks in extreme teams
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
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AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
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Artificial Intelligence
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IEEE Transactions on Computers
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Massively Multi-Agent Technology
Using Swarm-GAP for Distributed Task Allocation in Complex Scenarios
Massively Multi-Agent Technology
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IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
RoboCup Rescue as multiagent task allocation among teams: experiments with task interdependencies
Autonomous Agents and Multi-Agent Systems
Robocup rescue simulation competition: status report
RoboCup 2005
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SBIA'12 Proceedings of the 21st Brazilian conference on Advances in Artificial Intelligence
Weighted synergy graphs for effective team formation with heterogeneous ad hoc agents
Artificial Intelligence
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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.