The Computing of Digital Ecosystems
Gerard Briscoe and
Philippe De Wilde
Additional contact information
Gerard Briscoe: London School of Economics and Political Science, UK
Philippe De Wilde: Heriot-Watt University, UK
International Journal of Organizational and Collective Intelligence (IJOCI), 2010, vol. 1, issue 4, 1-17
A primary motivation this research in digital ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex and dynamic problems. However, the computing technologies that contribute to these properties have not been made explicit in digital ecosystems research. In this paper, the authors discuss how different computing technologies can contribute to providing the necessary self-organising features, including Multi-Agent Systems (MASs), Service-Oriented Architectures (SOAs), and distributed evolutionary computing (DEC). The potential for exploiting these properties in digital ecosystems is considered, suggesting how several key features of biological ecosystems can be exploited in Digital Ecosystems, and discussing how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, which consider the self-organised diversity of its evolving agent populations relative to the user request behaviour.
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/joci.2010100101 (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:igg:joci00:v:1:y:2010:i:4:p:1-17
Access Statistics for this article
More articles in International Journal of Organizational and Collective Intelligence (IJOCI) from IGI Global
Bibliographic data for series maintained by Journal Editor ().