Decentralised Dynamic Task Allocation Using Overlapping Potential Games

This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a stochastic game formulation of these problems in which tasks have varying hard deadlines and processing requirements. We then introduce a new technique for a...

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Bibliographic Details
Main Authors: Chapman, Archie (Author), Micillo, Rosa Anna (Author), Kota, Ramachandra (Author), Jennings, Nick (Author)
Format: Article
Language:English
Published: 2010-10.
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Summary:This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a stochastic game formulation of these problems in which tasks have varying hard deadlines and processing requirements. We then introduce a new technique for approximating this game using a series of static potential games, before detailing a decentralised method for solving the approximating games that uses the distributed stochastic algorithm. Finally, we discuss an implementation of our approach to a task allocation problem in the RoboCup Rescue disaster management simulator. The results show that our technique performs comparably to a centralised task scheduler (within 6% on average), and also, unlike its centralised counterpart, it is robust to restrictions on the agents' communication and observation ranges.