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Evolutionary Computation (EC) is one of the most relevant, better known and applied bio-inspired models of computations that shares its inspiration with the emerging field in formal language theory called Natural Computing (NC). NC is mainly focused on the computing capabilities of formal devices that abstract some natural complex phenomena. In general, NC (and EC) offers strong models for solving hard real-world problems inspired in the way in which some natural system performs some specific and difficult task. To apply EC, specifically, we have to translate our problem into a search across an appropriate space of candidate solutions. NC models are, in general, inherently parallel and able to reach better performance under some circumstances. NC is, therefore, currently being considered as an area in which one could find computer designs different from von Neumann architecture.

We want to relate those models and the area of processing natural and formal languages in two different ways:

1. Firstly, if we want to use NC models as real computers, we have to design programming languages and software engineering tools for them. Evolutionary Automatic Programming is a branch of EC that is focused in automatically writing programs and that could be a useful
start point for software engineering tools to apply to these models.
2. Secondly, we are convinced that the area of processing languages is a field where those new described technologies can offer good solutions and alternative frameworks to classic models.

Some of the best known bio-inspired models proposed in NC are Lindenmayer Systems, Eco-Grammar Systems, Colonies, Membrane Systems, Networks of Evolutionary Processors, Splicing Systems and Evolutionary Systems. These models share their bio-inspiration and expressive power with EC and other formal devices introduced in earlier times such as Cellular Automata, DNA computing or Genetic Algorithms. The discrete nature of their basic components and the results obtained by most of them, clearly show that they could be of great interest in the processing of natural and formal languages.
One of the main problems when we consider NC models as alternative architectures for building new computers is that there is almost no programming language and software engineering tool for them. This fact poses us new problems and tasks such as the simulation of the models on von Neumann computers and the proper tools for programming these new computers. The inherent parallelism of most of these models suggests the use of massive parallel platforms.
The results in this area have been quite theoretical. Our main goal is to bring together researchers from different realms - mathematics, computers science, computational linguistics, formal language theory - that have the aim to study such devices and to apply them to natural/formal language processing.

• Analysis and simulation of natural computers (including the implementation of EC algorithms)
• Natural computers programming (including automatic evolutionary programming)
• Natural language generation
• Environment and context description and management
• Dialogue modeling
• Speech recognition
• Simulations of language evolution
• Semantics and ontologies
• Parsing technologies In general, contributions on these natural computers and on any interaction between them and EC and natural/ formal languages will be welcome.

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