Digital ecosystems: Optimisation by a distributed intelligence

Gerard Briscoe*, Philippe De Wilde

*Corresponding author for this work

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

17 Citations (Scopus)


Can intelligence optimise Digital Ecosystems? How could a distributed intelligence interact with the ecosystem dynamics? Can the software components that are part of genetic selection be intelligent in themselves, as in an adaptive technology? We consider the effect of a distributed intelligence mechanism on the evolutionary and ecological dynamics of our Digital Ecosystem, which is the digital counterpart of a biological ecosystem for evolving software services in a distributed network. We investigate Neural Networks (NNs) and Support Vector Machines (SVM) for the learning based pattern recognition functionality of our distributed intelligence. Simulation results imply that the Digital Ecosystem performs better with the application of a distributed intelligence, marginally more effectively when powered by SVM than NNs. These results suggest that a distributed intelligence can contribute to optimising the operation of our Digital Ecosystem. © 2008 IEEE.

Original languageEnglish
Title of host publication2nd IEEE International Conference on Digital Ecosystems and Technologies, 2008
Number of pages6
ISBN (Electronic)978-1-4244-1490-1
ISBN (Print)978-1-4244-1489-5
Publication statusPublished - 2008
Event2nd IEEE International Conference on Digital Ecosystems and Technologies - Phitsanulok, Thailand
Duration: 26 Feb 200829 Feb 2008


Conference2nd IEEE International Conference on Digital Ecosystems and Technologies
Abbreviated titleDEST 2008


  • evolution
  • ecosystem
  • intelligence
  • distributed


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