Complex systems have been studied by researchers from every discipline: biology, chemistry, physics, sociology, mathematics and economics and more. Depending upon the discipline, complex systems theory has accrued many flavors. We are after a formal representation, a model that can predict the outcome of a complex adaptive system (CAS). In this article, we look at the nature of complexity, then provide a perspective based on discrete event systems (DEVS) theory. We pin down many of the shared features between CAS and artificial systems. We begin with an overview of network science showing how adaptive behavior in these scale-free networks can lead to emergence through stigmergy in CAS. We also address how both self-organization and emergence interplay in a CAS. We then build a case for the view that stigmergic systems are a special case of CAS. We then discuss DEVS levels of systems specifications and present the dynamic structure extensions of DEVS formalism that lends itself to a study of CAS and in turn, stigmergy. Finally, we address the shortcomings and the limitation of current DEVS extensions and propose the required augmentation to model stigmergy and CAS.
Giorgio BertiniResearch on society, culture, art, neuroscience, cognition, critical thinking, intelligence, creativity, autopoiesis, self-organization, rhizomes, complexity, systems, networks, leadership, sustainability, thinkers, futures ++
Academic SupportThe Learning Change Project is a personal not for profit and without sponsors multidisciplinary initiative to support academic activities. Use the files freely for your Courses or Research. To prepare Reading Lists explore the Category List or Search for the topic of your interest. If you need any support, contact me.
4000 Posts in this BlogFollow my Networks for recent Posts. For authors, date, publishers +metadata, view the source.
- Follow Learning Change on WordPress.com