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01336 am a22001573u 4500 |
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268518 |
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|a dc
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|a Chapman, Archie
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|a Micillo, Rosa Anna
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|a Kota, Ramachandra
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|a Jennings, Nick
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|a Decentralised Dynamic Task Allocation Using Overlapping Potential Games
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|c 2010-10.
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|z Get fulltext
|u https://eprints.soton.ac.uk/268518/1/ChapmanEtal_CJ2010.pdf
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|a 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.
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