Re-thinking simulation: a methodological approach for the application of data mining in agent-based modelling

Arroyo, Javier; Hassan, Samer; Gutiérrez, Celia; Pavón, Juán

doi:10.1007/s10588-010-9078-y

Cited by 18 publications

(12 citation statements)

References 17 publications

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“…For illustration, Remondino and Correndo (2006) presented a case study in which a biological phenomenon involving some species of cicadas was analyzed by performing multiple runs of simulations and aggregating the results. In another work, Arroyo et al (2010) proposed a methodological approach involving a data mining step to validate and improve the results of an agent-based model. They presented a case study in which cluster analysis was applied to validate simulation results of the 'MENTAT' model.…”

Section: Analyzing Agent-based Models: a Brief Surveymentioning

confidence: 99%

A scheme to analyze agent-based social simulations using exploratory data mining techniques

Patel

Abbasi

Saeed

et al. 2018

Complex Adapt Syst Model

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Exploring and understanding outputs from agent-based models is challenging due to a relatively higher number of parameters and multidimensionality of the generated data. We use a combination of exploratory and data mining techniques to understand data generated from an existing agent-based model to understand the model’s behavior and its sensitivity to initial configurations of its parameters. This is a step in the direction of an ongoing research in the social simulation community to incorporate more sophisticated techniques to better understand how different parameters and internal processes influence outcomes of agent-based models.

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Section: Analyzing Agent-based Models: a Brief Surveymentioning

confidence: 99%

A scheme to analyze agent-based social simulations using exploratory data mining techniques

Patel

Abbasi

Saeed

et al. 2018

Complex Adapt Syst Model

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“…This aspect of integration can be applied through Data-Driven Agent-Based Modelling that focuses on using data science in all aspects of ABMS, but especially analysis [96]. Sibertin-Blanc et al [97] apply this technique in an ABM of a river management program in France.…”

Section: Integration With Abmsmentioning

confidence: 99%

“…Arroyo et al [96] created an ABM through a data-driven approach and discuss applying clustering techniques to understand its output. The simulation was designed to represent changes in political and religious values in historic Spain, taking into account different groups of the population and their beliefs.…”

Section: Data Science and Abm Integrationmentioning

confidence: 99%

Case Study for the Return on Investment of Internet of Things Using Agent-Based Modelling and Data Science

Houston

Gooberman-Hill

Mathie

et al. 2017

Systems

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Abstract:As technology advances towards new paradigms such as the Internet of Things, there is a desire among business leaders for a reliable method to determine the value of supporting these ventures. Traditional simulation and analysis techniques cannot model the complex systems inherent in fields such as infrastructure asset management, or suffer from a lack of data on which to build a prediction. Agent-based modelling, through an integration with data science, presents an attractive simulation method to capture these underlying complexities and provide a solution. The aim of this work is to investigate this integration as a refined process for answering practical business questions. A specific case study is addressed to assess the return on investment of installing condition monitoring sensors on lift assets in a London Underground station. An agent-based model is developed for this purpose, supported by analysis from historical data. The simulation results demonstrate how returns can be achieved and highlight features induced as a result of stochasticity in the model. Suggestions of future research paths are additionally outlined.

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“…In [4] a methodological approach for multi agents modeling and simulation using data mining techniques was presented. The authors proposed an intensive use of these techniques of data mining to improve and develop agent-based models.…”

Section: Related Workmentioning

confidence: 99%

“…These studies are related to maintenance of aircraft engines [1], neurosciences [2], higher education [3], social sciences [4] and others.…”

Section: Introductionmentioning

confidence: 99%

How Data Mining Techniques Can Improve Simulation Studies

Saoud¹,

Boubetra²,

S³

2014

IJCTE

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Abstract-Researchers take years and even decades of observation in order to analyze socio-economic phenomenon. Whereas the agent-based modeling simulation (ABMS) provides a new issue by offering the possibility to create virtual societies in which individuals and organizations are directly represented with their observed interactions. As it is known simulation generates and consumes a large amount of data. The analysis of these data which may contain implicit and hidden information will always remain a very difficult phase in the ABMS. As a solution to this problematic, the use of data mining techniques can contribute to the right analysis of the phenomena that emerges in these systems. In this paper we aim the investigation of agent-based modeling simulation and data mining techniques.Index Terms-Agent-based modeling and simulation, data mining, analysis behaviors, emergence.

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Re-thinking simulation: a methodological approach for the application of data mining in agent-based modelling

Cited by 18 publications

References 17 publications

A scheme to analyze agent-based social simulations using exploratory data mining techniques

A scheme to analyze agent-based social simulations using exploratory data mining techniques

Case Study for the Return on Investment of Internet of Things Using Agent-Based Modelling and Data Science

How Data Mining Techniques Can Improve Simulation Studies

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