Digital Ecosystems: Optimisation by a Distributed Intelligence

TL;DR

This paper explores how distributed intelligence, such as neural networks and support vector machines, can enhance the performance and optimization of digital ecosystems that evolve software services in a networked environment.

Contribution

It introduces the integration of neural networks and support vector machines as distributed intelligence mechanisms within digital ecosystems, analyzing their impact on ecosystem dynamics and optimization.

Findings

Distributed intelligence improves ecosystem performance

Support Vector Machines outperform Neural Networks in this context

Enhanced ecosystem optimization observed with intelligent components

Abstract

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 and Support Vector Machine 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 Support Vector Machine than Neural Networks, and suggest that it can contribute to optimising the operation of our Digital Ecosystem.