Task Allocation in the RoboCup Rescue Simulation Domain: A Short Note
RoboCup 2001: Robot Soccer World Cup V
An asynchronous complete method for distributed constraint optimization
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Allocating tasks in extreme teams
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Analysis of Dynamic Task Allocation in Multi-Robot Systems
International Journal of Robotics Research
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For an interesting class of emerging applications, a large robot team will need to distributedly allocate many more tasks than there are robots, with dynamically appearing tasks and a limited ability to communicate. The LA-DCOP algorithm can conceptually handle both large-scale problems and multiple tasks per robot, but has key limitations when allocating spatially distributed tasks. In this paper, we extend LA-DCOP with several alternative acceptance rules for robots to determine whether to take on an additional task, given the interaction with the tasks it has already committed to. We show that these acceptance rules dramatically outperform a naive LA-DCOP implementation. In addition, we developed a technique that lets the robots use completely local knowledge to adjust their task acceptance criteria to get the best possible performance at a given communication bandwidth level.