Abstract
We present a novel decentralized approach to allocate agents to tasks whose costs increase over time. Our model accounts for both the natural growth of the tasks and the effort of the agents at containing such growth. The objective is to minimize the increase in task costs. We show how a distributed coordination algorithm, which is based on max-sum, can be formulated to include costs of tasks that grow over time. Considering growing costs enables our approach to solve a wider range of problems than existing methods. We compare our approach against state-of-the-art methods in both a simple simulation and RoboCup Rescue simulation.
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