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Decentralised Dynamic Task Allocation Using Overlapping Potential Games

Decentralised Dynamic Task Allocation Using Overlapping Potential Games
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 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.
1462 -1477
Chapman, Archie
2eac6920-2aff-49ab-8d8e-a0ea3e39ba60
Micillo, Rosa Anna
56810e45-e584-4e9a-8991-a9705a2cb70c
Kota, Ramachandra
a2b6c536-fa54-4d9e-8f3d-c3fb66f79b86
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Chapman, Archie
2eac6920-2aff-49ab-8d8e-a0ea3e39ba60
Micillo, Rosa Anna
56810e45-e584-4e9a-8991-a9705a2cb70c
Kota, Ramachandra
a2b6c536-fa54-4d9e-8f3d-c3fb66f79b86
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Chapman, Archie, Micillo, Rosa Anna, Kota, Ramachandra and Jennings, Nick (2010) Decentralised Dynamic Task Allocation Using Overlapping Potential Games. The Computer Journal, 53 (9), 1462 -1477. (doi:10.1093/comjnl/bxq023). (In Press)

Record type: Article

Abstract

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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Accepted/In Press date: October 2010
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 268518
URI: http://eprints.soton.ac.uk/id/eprint/268518
PURE UUID: cdc4314a-a395-466f-8824-4ce4d7a1c83c

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Date deposited: 18 Feb 2010 11:22
Last modified: 19 Jul 2019 22:15

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