  Creativity, or the ability to produce new useful ideas, is commonly
associated to the human being; but there are many other examples in nature
where this phenomenon can be observed. Inspired by this fact, in engineering
and particularly in computational sciences, many different models have been
developed to tackle a number of problems.
  Composing music, a form of art broadly present along the human history, is
the main topic addressed in this thesis. Taking advantage of the kind of ideas
that bring diversity and creativity to nature and computation, we present
Melomics: an algorithmic composition method based on evolutionary search. The
solutions have a genetic encoding based on formal grammars and these are
interpreted in a complex developmental process followed by a fitness
assessment, to produce valid music compositions in standard formats.
  The system has exhibited a high creative power and versatility to produce
music of different types and it has been tested, proving on many occasions the
outcome to be indistinguishable from the music made by human composers. The
system has also enabled the emergence of a set of completely novel
applications: from effective tools to help anyone to easily obtain the precise
music that they need, to radically new uses, such as adaptive music for
therapy, exercise, amusement and many others. It seems clear that automated
composition is an active research area and that countless new uses will be
discovered.
