Chapman, Archie, Micillo, Rosa Anna, Kota, Ramachandra and Jennings, Nick
Decentralised Dynamic Task Allocation Using Overlapping Potential Games
The Computer Journal, 53, (9), .
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.
||Agents, Interactions & Complexity
|October 2010||Accepted/In Press|
||18 Feb 2010 11:22
||17 Apr 2017 18:31
|Further Information:||Google Scholar|
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