On Formal Methods for Collective Adaptive System Engineering. {Scalable Approximated, Spatial} Analysis Techniques. Extended Abstract

In this extended abstract a view on the role of Formal Methods in System Engineering is briefly presented. Then two examples of useful analysis techniques based on solid mathematical theories are discussed as well as the software tools which have been built for supporting such techniques. The first technique is Scalable Approximated Population DTMC Model-checking. The second one is Spatial Model-checking for Closure Spaces. Both techniques have been developed in the context of the EU funded project QUANTICOL.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

On-the-fly PCTL fast mean-field approximated model-checking for self-organising coordination

Typical self-organising collective systems consist of a large number of interacting objects that coordinate their activities in a decentralised and often implicit way. Design of such systems is challenging and requires suitable, scalable analysis tools to check properties of proposed system designs before they are put into operation. We present a novel scalable, on-the-fly approximated model-checking procedure to verify bounded PCTL properties of selected individuals in the context of very large systems of independent interacting objects. The proposed procedure combines on-the-fly model-checking techniques with deterministic mean-field approximation in discrete time. The asymptotic correctness of the procedure is proven and a prototype implementation of the model-checker is presented. The potential of the verification approach is illustrated by its application on self-organising collective systems and an overview of remaining open issues and future extensions is provided

Linking complexity economics and systems thinking, with illustrative discussions of urban sustainability

The expanding research of complexity economics has been signalling its preference for a formal quantitative investigation of diverse interactions between heterogeneous agents at the lower, micro-level resulting in emergent, realistic socioeconomic dynamics at the higher, macro-level. However, there is scarcity in research that explicitly links complexity perspectives in economics with the systems thinking literature, despite these being highly compatible, with strong connections and common historical traces. We aim to address this gap by exploring commonalities and differences between the two bodies of knowledge, seen particularly through an economics lens. We argue for a hybrid approach, in that agent-based complexity perspectives in economics could more closely connect to two main systems thinking attributes: a macroscopic approach to analytically capturing the complex dynamics of systems, and an inter-subjective interpretivist dimension, when investigating complex social-economic order. Illustrative discussions of city sustainability are provided, with an emphasis on decarbonisation and residential energy demand aspects