Skip to main navigation Skip to search Skip to main content

A markovian agent model for fire propagation in outdoor environments

  • Davide Cerotti
  • , Marco Gribaudo
  • , Andrea Bobbio
  • , Carlos T. Calafate
  • , Pietro Manzoni

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Markovian Agent Models are a rather new modeling technique to deal with complex systems composed by a multitude of interacting entities, whose spatial location is also relevant in determining their interaction. An example of application to the study of outdoor fire propagation is provided. The dynamic of this phenomenon strongly depends both on the type of materials being incinerated and on the wind direction and intensity. Therefore, the ability of the model to correctly reproduce the fire propagation is closely related to the spatial dependent interactions among agents. Moreover, the model is flexible enough to analyse scenarios in variable environmental conditions, such as wind direction and intensity, and in the presence of fire-barriers which prevent flames from propagating.

Original languageEnglish
Title of host publicationComputer Performance Engineering - 7th European Performance Engineering Workshop, EPEW 2010, Proceedings
Pages131-146
Number of pages16
DOIs
Publication statusPublished - 2010
Event7th European Performance Engineering Workshop, EPEW 2010 - Bertinoro, Italy
Duration: 23 Sept 2010 → 24 Sept 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6342 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th European Performance Engineering Workshop, EPEW 2010
Country/TerritoryItaly
CityBertinoro
Period23/09/10 → 24/09/10

Keywords

  • Fire propagation
  • Markovian Agents
  • Performance evaluation

Fingerprint

Dive into the research topics of 'A markovian agent model for fire propagation in outdoor environments'. Together they form a unique fingerprint.

Cite this