A Markovian Agent Model for Fire Propagation in Outdoor Environments

Cerotti, Davide; Gribaudo, Marco; Bobbio, A.; Calafate, Carlos T.; Manzoni, Pietro

doi:10.1007/978-3-642-15784-4_9

Cited by 17 publications

(14 citation statements)

References 8 publications

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“…This language was introduced in [Feng and Hillston 2014] and provides a high-level modelling language for the multi-message multi-class Markovian agent modelling framework of [Cerotti et al 2010]. PALOMA has been revised since [Feng and Hillston 2014] in order to enhance the expressiveness of the language whilst also making model descriptions more compact.…”

Section: Introductionmentioning

confidence: 99%

Automatic Moment-Closure Approximation of Spatially Distributed Collective Adaptive Systems

Feng

Hillston

Galpin

2016

ACM Trans. Model. Comput. Simul.

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Spatially distributed collective adaptive systems are an important class of systems, which pose significant challenges to modelling due to the size and complexity of their state spaces. This problem is acute when the dynamic behaviour of the system must be captured, for example in order to predict system performance. In this paper we present an abstraction technique which automatically derives a moment-closure approximation of the dynamic behaviour of a spatially distributed collective adaptive system from a discrete representation of the entities involved. The moment-closure technique is demonstrated to give accurate estimates of dynamic behaviour, although the number of ordinary differential equations generated for the second order joint moments can grow large in some cases. For these cases, we propose a rigorous model reduction technique and demonstrate its use to substantially reduce the computational effort with only limited impact on the accuracy if the reduction threshold is set appropriately. All the techniques reported in this paper are implemented in a tool which is freely available for download.

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Section: Introductionmentioning

confidence: 99%

Automatic Moment-Closure Approximation of Spatially Distributed Collective Adaptive Systems

Feng

Hillston

Galpin

2016

ACM Trans. Model. Comput. Simul.

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“…Patch models have been used to model information transmission between mobile nodes [17,94,35]. Forest fires: Propagation of forest fires is investigated using Multi-class Multi-type Markovian Agent Model (M 2 MAM) [16]. The approach models individual agents in discrete space and from this, a patch ODE model is derived.…”

Section: Applications Of Discrete Space Modelsmentioning

confidence: 99%

Spatial Representations and Analysis Techniques

Galpin

2016

Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems

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Abstract. Space plays an important role in the dynamics of collective adaptive systems (CAS). There are choices between representations to be made when we model these systems with space included explicitly, rather than being abstracted away. Since CAS often involve a large number of agents or components, we focus on scalable modelling and analysis of these models, which may involve approximation techniques. Discrete and continuous space are considered, for both models of individuals and models of populations. The aim of this tutorial is to provide an overview that supports decisions in modelling systems that involve space.

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“…In this section, we briefly introduce the key concepts of M 2 MAMs, originally presented by Cerrotti et al in [1]. M 2 MAMs consist of a collection of Markov agents (MAs) distributed over space, which is represented by a finite set of locations.…”

Section: Mammentioning

confidence: 99%

“…Following [1], we use MA c ( ) to denote a MA of class c in location . A MA c ( ) can be defined as a tuple…”

Section: Mammentioning

confidence: 99%

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PALOMA: A Process Algebra for Located Markovian Agents

Feng

Hillston

2014

Lecture Notes in Computer Science

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Abstract. We present a novel stochastic process algebra that allows the expression of models representing systems comprised of populations of agents distributed over space, where the relative positions of agents influence their interaction. This language, PALOMA, is given both discrete and continuous semantics and it captures multi-class, multi-message Markovian agent models (M 2 MAM). Here we present the definition of the language and both forms of semantics, and demonstrate the use of the language to model a flu epidemic under various quarantine regimes.

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A Markovian Agent Model for Fire Propagation in Outdoor Environments

Cited by 17 publications

References 8 publications

Automatic Moment-Closure Approximation of Spatially Distributed Collective Adaptive Systems

Automatic Moment-Closure Approximation of Spatially Distributed Collective Adaptive Systems

Spatial Representations and Analysis Techniques

PALOMA: A Process Algebra for Located Markovian Agents

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