Skip to main content

Decentralised Task Allocation Under Space, Time and Communication Constraints in Disaster Domains

  • Chapter
  • First Online:
Smart Modeling and Simulation for Complex Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 564))

Abstract

The coordination of dynamic task allocation based on available resources is a very challenging issue in disaster domains under time, space and communication constraints. In addition, it is also very hard or even impossible to achieve tasks allocation in a centralised manner with the global knowledge of such an environment. This paper presents a novel decentralised coordination approach for dynamic task allocation by considering space, time and communication constraints in a disaster domain, and workloads and priorities of different tasks. In this approach, a group formation mechanism is proposed to help agents with limited communication ranges to achieve efficient task allocation in a group through cooperation. The overall task allocation is achieved through distributed coordination in each dynamic group without a central control mechanism to reflect real life situations in a general disaster domain. The experiment results show that the proposed approach outperforms other decentralised approaches, in disaster domains under space, time and communication constrains.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Barbulescu, L., Rubinstein, Z.B., Smith, S.F., Zimmerman, T.L.: Distributed coordination of mobile agent teams: the advantage of planning ahead. In: AAMAS ’10, pp. 1331–1338, Richland (2010)

    Google Scholar 

  2. Chapman, A.C., Micillo, R.A., Kota, R., Jennings, N.R.: Decentralised dynamic task allocation: a practical game: theoretic approach. In: AAMAS ’09, vol. 2 (2009)

    Google Scholar 

  3. Farinelli, A., Rogers, A., Petcu, A., Jennings, N.R.: Decentralised coordination of low-power embedded devices using the max-sum algorithm. In: AAMAS ’08, vol. 2, pp. 639–646, Estoril (2008)

    Google Scholar 

  4. Gordon, G.J., Hong, S.A., Dudík, M.: First-order mixed integer linear programming. In: UAI ’09, pp. 213–222. AUAI Press, Arlington (2009)

    Google Scholar 

  5. Koes, M., Nourbakhsh, I., Sycara, K.: Heterogeneous multirobot coordination with spatial and temporal constraints. In: AAAI ’05, pp. 1292–1297. AAAI Press, Menlo Park (2005)

    Google Scholar 

  6. Lesser, V.: Cooperative multiagent systems: A personal view of the state of the art. IEEE Trans. Knowl. Data Eng. 11, 133–142 (1999)

    Article  Google Scholar 

  7. Maheswaran, R., Szekely, P., Becker, M., Fitzpatrick, S., Gati, G., Jin, J., Neches, R., Noori, N., Rogers, C., Sanchez, R., Smyth, K., Buskirk, C.V.: Look where you can see: Predictability & criticality metrics for coordination in complex environments. In: AAMAS ’08 (2008)

    Google Scholar 

  8. Musliner, D.J., Goldman, R.P.: Coordinated plan management using multiagent mdps. In: AAAI ’06, pp. 73–80. AAAI Press, Menlo Park (2006)

    Google Scholar 

  9. Ramamritham, K., Stankovic, J.A., Zhao, W.: Distributed scheduling of tasks with deadlines and resource requirements. IEEE Trans. Comput. 38(8), 1110–1123 (1989)

    Article  Google Scholar 

  10. Ramchurn, S.D., Farinelli, A., Macarthur, K.S., Jennings, N.R.: Decentralized coordination in robocup rescue. Comput. J. 53(9), 1447–1461 (2010)

    Article  Google Scholar 

  11. Ramchurn, S.D., Polukarov, M., Farinelli, A., Truong, C., Jennings, N.R.: Coalition formation with spatial and temporal constraints. In: AAMAS 2010, pp. 1181–1188 (2010)

    Google Scholar 

  12. Ren, F., Sim, K.M.: Adaptive conceding strategies for automated trading agents in dynamic, open markets. Decis. Support Syst. 48(2), 331–341 (2009)

    Google Scholar 

  13. Smith, S.F., Gallagher, A., Zimmerman, T.: Distributed management of flexible times schedules. In: AAMAS ’07, vol. 74, pp. 1–8. ACM, New York (2007)

    Google Scholar 

  14. Taxicab geometry (2003). https://en.wikipedia.org/wiki/Centroid

  15. Vinyals, M., Pujol, M.: Divide-and-coordinate: Dcops by agreement. In: AAMAS’10, pp. 149–156 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xing Su .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Japan

About this chapter

Cite this chapter

Su, X., Zhang, M., Bai, Q. (2015). Decentralised Task Allocation Under Space, Time and Communication Constraints in Disaster Domains. In: Bai, Q., Ren, F., Zhang, M., Ito, T., Tang, X. (eds) Smart Modeling and Simulation for Complex Systems. Studies in Computational Intelligence, vol 564. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55209-3_4

Download citation

  • DOI: https://doi.org/10.1007/978-4-431-55209-3_4

  • Published:

  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-55208-6

  • Online ISBN: 978-4-431-55209-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics