Computing by Nature

First, the track is devoted to standard algorithms running on standard computers, but inspired by the behaviour of processes taking place in nature, such as artificial neural networks exploring computational concepts related to some characteristics of the brain, or evolutionary genetic algorithms inspired by biological evolution. Today these areas are mature, with useful applications to optimization, machine learning and control; properties of hybrid artificial models are explored and intriguing experiments on hybrid networks are proposed, in which living neurons interact with digital model neurons. Second, this area of interest concerns algorithms that are based on "primitive procedures" or data given to us by Nature, such as quantum or DNA computing. So far, the results in this area are prevalently of theoretical interest. Nevertheless, they seem to open very promising perspectives in the applications.

The list of topics include (but is not limited to):

• ant colony optimization
• artificial immune system
• bioinformatics
• DNA computing
• evolutionary computation
• hybrid models, neural, fuzzy, or genetic
• membrane computing
• neural networks
• quantum computing
• swarm intelligence