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ature-inspired algorithms such as genetic algorithms, particle swarm optimisation and ant colony algorithms are the solution technique of choice for some problems. Furthermore, their population-based 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 limits their usefulness of these implementations to industry’s direction of increasing distribution, decentralisation and adaptability. Emerging computing environments such as autonomic computing, ubiquitous computing, Peer-toPeer 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, their design techniques and necessary infrastructures into such emerging computing environments. Topics of interest include:

Special issue of Multi-Agent and Grid Systems – An International Journal