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Bushfire BLOCKS: a modular agent-based simulation

Published:10 May 2010Publication History

ABSTRACT

Bushfire BLOCKS is a modular, distributed, agent-based simulation for exploring and informing bushfire response strategies. Separate independent modules capture the fire spread, evacuation of traffic and human behaviour such as the decision whether to remain at property. These modules have been developed largely independently, using paradigms and data models appropriate to their individual purpose. Modules are integrated into a single global simulation via central services for managing time advancement and access to shared variables. Execution is distributed, with modules running on different machines, whilst a custom interface enables viewing and control from one screen. The underlying architecture of this system facilitates extension of individual modules and addition of new modules, with limited alteration to other modules.

References

  1. R. M. Fujimoto. Time Management in The High Level Architecture. Simulation, 71(6):388--400, 1998.Google ScholarGoogle ScholarCross RefCross Ref
  2. G. Gilbert and K. Troitzsch. Simulation for the social scientist. Open University Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. D. Scerri, S. Hickmott, L. Padgham, and A. Drogoul. An architecture for modular distributed simulation with agent-based models. In Ninth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS '10). ACM, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Bushfire BLOCKS: a modular agent-based simulation

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    • Published in

      cover image ACM Other conferences
      AAMAS '10: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
      May 2010
      1578 pages
      ISBN:9780982657119

      Publisher

      International Foundation for Autonomous Agents and Multiagent Systems

      Richland, SC

      Publication History

      • Published: 10 May 2010

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      • research-article

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      Overall Acceptance Rate1,155of5,036submissions,23%

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