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 ... [more] 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.

DOI

Bibtex Entry

@inproceedings{Wright2013,
  author    = "Wright, Chris J. and McMinn, Phil and Gallardo, Julio",
  title     = "Towards the Automatic Identification of Faulty Multi-Agent Based Simulation Runs Using {MASTER}",
  booktitle = "Multi-Agent-Based Simulation XIII --- International Workshop on Multi-Agent Simulation (MABS 2012)",
  series    = "Lecture Notes in Artificial Intelligence",
  volume    = "7838",
  pages     = "153--172",
  year      = "2013",
  publisher = "Springer"
}