A roadmap of nature-inspired systems research and development

Nature-inspired algorithms such as genetic algorithms, particle swarm optimisation and ant colony algorithms have successfully solved computer science problems of search and optimisation. The initial implementations of these techniques focused on static problems solved on single machines. These have been extended by adding parallelisation capabilities in the vein of distributed computing with a centralised master/slave approach. However, the natural systems on which nature-inspired algorithms are based possess many additional characteristics that are of potential benefit within computing environments. In this paper, we discuss the benefits of nature-inspired techniques within modern and emerging computing environments. Software entities within these environments execute and interact in a fashion that is parallel, asynchronous, and decentralised. Given that the natural environment is in itself parallel, asynchronous and decentralised, nature-inspired techniques are an excellent fit for computing environments that exhibit these characteristics. Future research challenges for nature-inspired techniques within emerging computing environments are also discussed.