Name
Abstract | ||
|---|---|---|
This paper reports on a novel decentralized 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 decentralized 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 centralized task scheduler (within 6% on average), and also, unlike its centralized counterpart, it is robust to restrictions on the agents’ communication and observation ranges. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1093/comjnl/bxq023 | Comput. J. |
Keywords | Field | DocType |
overlapping potential games,dynamic task allocation problem,decentralized dynamic task allocation,approximating game,decentralized method,centralized counterpart,centralized task scheduler,stochastic algorithm,task allocation problem,novel decentralized technique,static potential game,new technique | Computer science,Emergency management,Theoretical computer science,Schedule,Stochastic game,Distributed computing | Journal |
Volume | Issue | ISSN |
53 | 9 | 0010-4620 |
Citations | PageRank | References |
10 | 0.55 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Archie Chapman | 1 | 172 | 19.56 |
| Rosa Anna Micillo | 2 | 43 | 3.48 |
| Ramachandra Kota | 3 | 196 | 14.19 |
| Nicholas R. Jennings | 4 | 19348 | 1564.35 |