Modeling civil violence: An agent-based computational approach

Epstein, Joshua M.

doi:10.1073/pnas.092080199

Cited by 395 publications

(361 citation statements)

References 10 publications

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“…Various social phenomena have been investigated using agent-based models that are not easily modelled using other approaches (Macy and Willer, 2002;Gilbert and Troitzsch, 2005). Theoretical applications include social emergence (Sawyer, 2005), the emergence of cooperation (Axelrod, 1997), the generation of social instability (Epstein, 2002), and the collective behaviour of people in crowds (Pan et al, 2007). Sakoda (1971) formulated one of the first social agent-based models, the Checkerboard Model, which relied on a cellular automaton.…”

Section: Applications Overviewmentioning

confidence: 99%

Tutorial on agent-based modelling and simulation

Macal

North

2010

Journal of Simulation

1,280

630

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Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling systems composed of autonomous, interacting agents. Agent-based modelling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modelling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.

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Section: Applications Overviewmentioning

confidence: 99%

Tutorial on agent-based modelling and simulation

Macal

North

2010

Journal of Simulation

1,280

630

View full text Add to dashboard Cite

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“…By formalising a few simple rules, SUGAR-SCAPE allowed for the experimental investigation of some of the theorised micro-level mechanisms responsible for the dynamics of civil war. Subsequently, Epstein (2002) produced the first ABM simulations of armed conflict. These simulations modelled the emergence of rebellion and ethnic-cleansing behaviour as a product of the rebel agent's perception of the police force numbers (i.e.…”

Section: Previous Numerical Models Of Civil Conflictmentioning

confidence: 99%

Potential uses of Numerical Simulation for the Modelling of Civil Conflict

Burton

Johnson

Braithwaite³

2017

Peace Economics, Peace Science and Public Policy

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This paper explores ways in which civil conflict can be simulated using numerical methods. A general two-party model of conflict is developed by extending an approach proposed by [Christia, F., (2012), Alliance Formation in Civil Wars, Cambridge University Press, New York], which is based on a metric of the 'relative power' that exists between the state and a rebel group. Various definitions of relative power are considered and one of these is chosen to illustrate different types of two-sided armed conflict, namely direct-fire, guerrilla and asymmetric warfare. The additional suggestion of Christia that random or stochastic events can lead to unexpected conflict outcomes is also further extended in this paper. The inclusion in the model of terms describing concurrent rebel recruitment of civilians and state deployment of troops are then described. Examples are presented for various hypothetical cases. It is demonstrated that numerical simulation techniques have great potential for modelling civil war. The Christia approach is shown to provide an excellent basis from which numerical models of civil conflict can be built and from which the progress of a conflict can usefully be visualised graphically.

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“…Mathematical modelling is a newcomer in the fight against crime, with a number of models being proposed during the last five years that use a variety of approaches to model crime. These vary from agentbased models [5,13], population dynamics models [16] and epidemiological models [23] to game-theoretic [14,19] and probabilistic models [7,15,22].…”

Section: Introductionmentioning

confidence: 99%

A mathematical model of serious and minor criminal activity

Lacey

Tsardakas

2016

Eur. J. Appl. Math

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Using mathematical methods to understand and model crime is a recent idea that has drawn considerable attention from researchers during the last five years. From the plethora of models that have been proposed, perhaps the most successful one has been a diffusion-type differential equations model that describes how the number of criminals evolves in a specific area. We propose a more detailed form of this model that allows for two distinct criminal types associated with major and minor crime. Additionally, we examine a stochastic variant of the model that represents more realistically the 'generation' of new criminals. Numerical solutions from both models are presented and compared with actual crime data for the Greater Manchester area. Agreement between simulations and actual data is satisfactory. A preliminary statistical analysis of the data also supports the model's potential to describe crime.

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Modeling civil violence: An agent-based computational approach

Cited by 395 publications

References 10 publications

Tutorial on agent-based modelling and simulation

Tutorial on agent-based modelling and simulation

Potential uses of Numerical Simulation for the Modelling of Civil Conflict

A mathematical model of serious and minor criminal activity

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