Special issue on Nature-inspired systems for parallel, asynchronous and decentralised environments
Enda Ridge, Edward Curry, Daniel Kudenko⋆, Dimitar Kazakov · Multiagent and Grid Systems · 2007
Nature-inspired algorithms such as genetic algorithms, particle swarm optimisation and ant colony algorithms are the state-of-the-art solution technique for some problems. Furthermore, their populationbased stochastic search approach promises desirable algorithm features such as anytime decentralised solution and robustness to problem change. However, the efficient pursuit of more accurate solutions leads researchers to appeal to centralised, highly tuned and sequential implementations that are only loosely related to their successful natural counterparts. This renders them brittle in the face of the dynamism of changing problem specifications and operating conditions and limits their usefulness to industry’s direction of increasing distribution, decentralisation and adaptability. Emerging computing environments such as autonomic computing, ubiquitous computing, Peer-to-Peer systems, the Grid and the Semantic Web demand the interaction of large numbers of decentralised, parallel, asynchronous, and distributed software entities in a standardised fashion. If nature-inspired algorithms are to make an impact on these emerging computing environments, disciplined scientific and engineering investigations must be undertaken into the successful transfer of these algorithms, techniques and infrastructures into such environments. 2. Contributions