Abstract
The goal of engineering self-organising emergent systems is to acquire a macroscopic system behaviour solely from autonomous local activity and interaction. Due to the non-deterministic nature of such systems, it is hard to guarantee that the required macroscopic behaviour is achieved and maintained. Before even considering a self-organising emergent system in an industrial context, e.g. for Automated Guided Vehicle (AGV) transportation systems, such guarantees are needed. An empirical analysis approach is proposed that combines realistic agent-based simulations with existing scientific numerical algorithms for analysing the macroscopic behaviour. The numerical algorithm itself obtains the analysis results on the fly by steering and accelerating the simulation process according to the algorithm’s goal. The approach is feasible, compared to formal proofs, and leads to more reliable and valuable results, compared to mere observation of simulation results. Also, the approach allows to systematically analyse the macroscopic behaviour to acquire macroscopic guarantees and feedback that can be used by an engineering process to iteratively shape a self-organising emergent solution.
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De Wolf, T., Holvoet, T., Samaey, G. (2006). Development of Self-organising Emergent Applications with Simulation-Based Numerical Analysis. In: Brueckner, S.A., Di Marzo Serugendo, G., Hales, D., Zambonelli, F. (eds) Engineering Self-Organising Systems. ESOA 2005. Lecture Notes in Computer Science(), vol 3910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11734697_11
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DOI: https://doi.org/10.1007/11734697_11
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