Abstract
Testing a multi-agent based model is a tedious process that involves generating very many simulation runs, for example as a result of a parameter sweep. In practice, each simulation run must be inspected manually to gain complete confidence that the agent-based model has been implemented correctly and is operating according to expectations. We present MASTER, a tool which aims to semi-automatically detect when a simulation run has deviated from “normal” behaviour. A simulation run is flagged as “suspicious” when certain parameters traverse normal bounds determined by the modeller. These bounds are defined in reference to a small series of actual executions of the model deemed to be correct. The operation of MASTER is presented with two case studies, the first with the well-known “flockers” model supplied with the popular MASON agent-based modelling toolkit, and the second a skin tissue model written using another toolkit—FLAME.
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Wright, C.J., McMinn, P., Gallardo, J. (2013). Towards the Automatic Identification of Faulty Multi-Agent Based Simulation Runs Using MASTER. In: Giardini, F., Amblard, F. (eds) Multi-Agent-Based Simulation XIII. MABS 2012. Lecture Notes in Computer Science(), vol 7838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38859-0_11
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DOI: https://doi.org/10.1007/978-3-642-38859-0_11
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