ABSTRACT
Consequently, the description of modern computation methods with classical formal models can be in many cases inadequately complicated. Nonetheless, this does not mean that the proposed jumping finite automata can or should properly cover all needs of discontinuous information processing. Indeed, there are many formal models that try to adequately capture different parts of this phenomenon. This diversity stems from the fact that, with these new models, we are trying to move some complex parts of the behavior of the computation methods into the core structure of the models. As a result, these new models are then more suited for specific tasks rather than for general purpose computing. This chapter presents two biologically oriented case studies. First, it describes a simple case study that suggests how to make use of jumping scattered context derivation in DNA processing. Then, within the framework of genetic algorithms, the chapter sketches an application of pure jumping grammars.
