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\( \texttt {MC} ^ \texttt {2} \texttt {MABS} \): A Monte Carlo Model Checker for Multiagent-Based Simulations

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Multi-Agent Based Simulation XVI (MABS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9568))

Abstract

Agent-based simulation has shown great success for the study of complex adaptive systems and could in many areas show advantages over traditional analytical methods. Due to their internal complexity, however, agent-based simulations are notoriously difficult to verify and validate.

This paper presents \( \texttt {MC} ^ \texttt {2} \texttt {MABS} \), a Monte Carlo Model Checker for Multiagent-Based Simulations. It incorporates the idea of statistical runtime verification, a combination of statistical model checking and runtime verification, and is tailored to the approximate verification of complex agent-based simulations. We provide a description of the underlying theory together with design decisions, an architectural overview, and implementation details. The performance of \( \texttt {MC} ^ \texttt {2} \texttt {MABS} \) in terms of both runtime consumption and memory allocation is evaluated against a set of example properties.

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Notes

  1. 1.

    McKelvey refers to this link as the model’s ontological adequacy [31].

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Authors and Affiliations

  1. Department of Informatics, King’s College London, London, UK

    Benjamin Herd, Simon Miles, Peter McBurney & Michael Luck

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  1. Benjamin Herd
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  2. Simon Miles
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Correspondence to Benjamin Herd .

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Editors and Affiliations

  1. Capitole, University Toulouse 1, Toulouse Cedex 9, France

    Benoit Gaudou

  2. Escola Politécnica, Universidade de Sao Paulo, São Paulo, Brazil

    Jaime Simão Sichman

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Herd, B., Miles, S., McBurney, P., Luck, M. (2016). \( \texttt {MC} ^ \texttt {2} \texttt {MABS} \): A Monte Carlo Model Checker for Multiagent-Based Simulations. In: Gaudou, B., Sichman, J. (eds) Multi-Agent Based Simulation XVI. MABS 2015. Lecture Notes in Computer Science(), vol 9568. Springer, Cham. https://doi.org/10.1007/978-3-319-31447-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-31447-1_3

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