Computing of applied digital ecosystems

Gerard Briscoe, Philippe De Wilde

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)


A primary motivation for our 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, dynamic problems. However, the computing technologies that contribute to these properties have not been made explicit in digital ecosystems research. Here, we 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, considering the self-organised diversity of its evolving agent populations relative to the user request behaviour. Copyright 2009 ACM.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Management of Emergent Digital EcoSystems, MEDES '09
Number of pages8
Publication statusPublished - 2009
Event1st ACM International Conference on Management of Emergent Digital EcoSystems - Lyon, France
Duration: 27 Oct 200930 Oct 2009


Conference1st ACM International Conference on Management of Emergent Digital EcoSystems
Abbreviated titleMEDES '09


  • Distributed evolutionary computing
  • Ecosystem-oriented architectures
  • Multi-agent systems
  • Service-oriented architectures


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