A Multiobjective Optimisation Approach for Dynamic Inference and Refinement of Agent-Based Model Specifications

by Salem Adra, Mariam Kiran, Phil McMinn and Neil Walkinshaw

Congress on Evolutionary Computation (CEC 2011)



Despite their increasing popularity, agent-based models are hard to test, and so far no established testing technique has been devised for this kind of software applications. Reverse engineering an agent-based model specification from model simulations can help establish a confidence level about the implemented model and in some cases reveal discrepancies between observed and normal or expected behaviour. In this study, a multiobjective optimisation technique based on a simple random search algorithm is deployed to dynamically infer and refine the specification of three agent-based models from their simulations. The multiobjective optimisation technique also incorporates a dynamic invariant detection technique which ... [more]


Reference

Salem Adra, Mariam Kiran, Phil McMinn and Neil Walkinshaw. A Multiobjective Optimisation Approach for Dynamic Inference and Refinement of Agent-Based Model Specifications. Congress on Evolutionary Computation (CEC 2011), pp. 2237–2244, 2011


Bibtex Entry
@inproceedings{Adra2011,
  author    = "Adra, Salem and Kiran, Mariam and McMinn, Phil and Walkinshaw, Neil",
  title     = "A Multiobjective Optimisation Approach for Dynamic Inference and Refinement of Agent-Based Model Specifications",
  booktitle = "Congress on Evolutionary Computation (CEC 2011)",
  pages     = "2237--2244",
  year      = "2011",
  publisher = "IEEE"
}