Latest revision as of 06:23, 2 February 2021

Abstract

Complex, natural, social, technological and economic systems have recently given rise to the need of a new paradigm for computational systems that are adaptive, can self-organise and exhibit emergent behaviour. The design of such systems concerns a homogeneous set of agents in which each agent receives an input and has to map it to a ‘good’ output, and where self-organisation emerges from the interaction between agents. Although general and simple, this concept is representative for a very wide spectrum of applications such as protocol design for large computer networks, design of collective robotics, and automative traffic engineering. Surprisingly, only a handful of recent research is aimed at a domain-independent (or: general) design of such systems. We propose as the solution for the design-problem a framework that tackles the local (agent) level formally and the global (system) level empirically. This allows us to do rigorous formal verification of the behaviour of the individual agents, as well as large-scale empirical validation of the system as a whole. Besides, it exploits the specific advantages of the approaches regarding the scale of the system: formalisation is good for small systems, while simulation works well for (very) large systems. The objective of this paper is to further develop and exploit the idea of combining a formal approach on the agent level and an empirical approach on the system level in self-organisation.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.7148/2009-0166-0172

• http://pdfs.semanticscholar.org/8e53/6aac82c4c69a30cc5179963d55f971354e37.pdf

• http://www.scs-europe.net/conf/ecms2009/ecms2009%20CD/ecms2009%20accepted%20papers/abs_0076_aee3878f.pdf,

https://www.cs.vu.nl/~schut/pubs/Schut/2009b.pdf,

http://www.scs-europe.net/dlib/2009/2009-0166.htm,

https://dblp.uni-trier.de/db/conf/ecms/ecms2009.html#SchutF09,

http://www.cs.vu.nl/~schut/pubs/Schut/2009b.pdf,

https://academic.microsoft.com/#/detail/2090583867