RatKit: Repeatable Automated Testing Toolkit for Agent-Based Modeling and Simulation

Cakirlar, Ibrahim; Gürcan, Önder; Dikenelli, Oğuz; Bora, Şebnem

doi:10.1007/978-3-319-14627-0_2

Cited by 3 publications

(1 citation statement)

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“…In the ABS community, a number of testing and monitoring approaches have been presented [6,39,32]. Most of these approaches are based on top of existing modelling frameworks such as Repast or Mason; consequently, correctness properties (in the form of test cases) are formulated in the target language, typically in Java.…”

Section: Related Workmentioning

confidence: 99%

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

Herd

Miles

McBurney

et al. 2016

Multi-Agent Based Simulation XVI

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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 MC 2 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 MC 2 MABS in terms of both runtime consumption and memory allocation is evaluated against a set of example properties.

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Section: Related Workmentioning

confidence: 99%