On the Role of Simulation in the Engineering of Self-Organising Systems: Detecting Abnormal Behaviour in MAS

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Luca Gardelli, Mirko Viroli, Andrea Omicini
Flavio Corradini, Flavio De Paoli, Emanuela Merelli, Andrea Omicini (eds.)
AI*IA/TABOO Joint Workshop “Dagli oggetti agli agenti: simulazione e analisi formale di sistemi complessi” (WOA 2005), pages 85–90
Pitagora Editrice Bologna, Camerino, MC, Italy
November 2005

The intrinsic complexity of self-organising multi-agent systems calls for the use of formal methods to predict global system evolutions at early stages of the design process. In particular, we evaluate the use of simulations of high-level system models to analyse properties of a design, which can anticipate the detection of wrong design choices and the tuning of system parameters, so as to rapidly converge to given overall requirements and performance factors.

We take abnormal behaviour detection as a case, and devise an architecture inspired by principles from human immune systems. This is based on the TuCSoN infrastructure, which provides agents with an environment of artefacts—most notably coordination artefacts and agent coordination contexts. We then use stochastic π-calculus for specifying and running quantitative, large-scale simulations, which allow us to verify the basic applicability of our ID and obtain a preliminary set of its main working parameters.

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page_white_powerpointOn the Role of Simulation in the Engineering of Self-Organising Systems: Detecting Abnormal Behaviour in MAS (WOA 2005, 15/11/2005) — Andrea Omicini (Luca Gardelli, Mirko Viroli, Andrea Omicini)