Towards the Automatic Identification of Faulty Multi-Agent Based Simulation Runs Using MASTER

  • Chris J. Wright
  • Phil McMinn
  • Julio Gallardo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7838)


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.


Tracker Code Parameter Sweep Property Violation Public Class Equivalent Mutant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chris J. Wright
    • 1
  • Phil McMinn
    • 1
  • Julio Gallardo
    • 1
  1. 1.Department of Computer ScienceUniversity of SheffieldPortobelloUK

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