© B. Herd, S. Miles, P. McBurney, M. Luck. Department of Informatics, King’s Co llege London Approximate verification of swarm-based systems: a vision and preliminary results Benjamin Herd, Simon Miles, Peter McBurney, Michael Luck Department of Informatics, King´s College London London, UK Abstract Swarm-based systems, i.e. systems comprising multiple simple, autonomous and interacting components, have become increasingly important. With their decentralised architecture, their ability to self-organise and to exhibit complex emergent behaviour, good scalability and support for inherent fault tol- erance due to a high level of redundancy, they offer characteristics which are particularly interesting for the construction of safety-critical systems. At the same time, swarms are notoriously difficult to engineer, to understand and to control. Emergent phenomena are, by definition, irreducible to the properties of the con- stituents which severely constrains predictability. Especially in safety-critical areas, however, a clear understanding of the future dynamics of the system is indispensable. In this paper we show how agent-based simulation in combination with statistical verification can help to understand and quantify the likelihood of emergent swarm behaviours on different observational levels. We illustrate the idea with a simple case study from the area of swarm robotics. 1 Introduction Swarm-based systems — systems comprising a possibly large number of interact- ing and autonomous components which collaborate in order to achieve a common goal — have become increasingly important. Inspired by nature, the principle of swarm intelligence provides a powerful paradigm for the construction of fully decentralised systems. As opposed to other multiagent systems, swarms are typi- cally composed of very simple individual components. Instead of being built into the system explicitly, the complex behaviour that can be observed at the macro level emerges from the actions and interactions of the constituents. Due to their lack of a central coordination mechanism, swarm-based systems typically offer a high level of scalability and fault tolerance. A high level of redundancy, the capa- bility to self-organise and robustness are further characteristics which make swarm-based systems highly attractive for application in safety-critical areas (Winfield et al. 2006).