Self-Organisation of Evolving Agent Populations in Digital Ecosystems
This work addresses modeling digital ecosystems for researchers, but appears incremental as it extends existing definitions.
The paper studied self-organizing behavior in digital ecosystems by extending definitions for complexity, stability, and diversity, and presented experimental results.
We investigate the self-organising behaviour of Digital Ecosystems, because a primary motivation for our research is to exploit the self-organising properties of biological ecosystems. We extended a definition for the complexity, grounded in the biological sciences, providing a measure of the information in an organism's genome. Next, we extended a definition for the stability, originating from the computer sciences, based upon convergence to an equilibrium distribution. Finally, we investigated a definition for the diversity, relative to the selection pressures provided by the user requests. We conclude with a summary and discussion of the achievements, including the experimental results.