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.
翻译:创造或产生新的有用思想的能力通常与人息息相关;但是在自然界中有许多其他例子可以观察到这种现象。受这个事实的启发,在工程学,特别是在计算科学中,已经开发了许多不同的模型来解决许多问题。结合音乐(一种在人类历史中广泛存在的艺术形式)是本论文讨论的主要专题。利用将多样性和创造力带入自然和计算的各种想法,我们介绍了Melomics:一种基于进化搜索的算法构成方法。解决方案有一个基于正式语法的遗传编码,这些方法在复杂的发展过程中被解释,随后进行健康评估,以产生有效的音乐组成标准格式。这个系统展示了一种很高的创造性和多功能来制作不同类型音乐,并且已经测试了它。它在许多场合证明其结果与人类作曲家的音乐不同。这个系统还使得一套完全新颖的应用得以出现:从有效的工具到帮助任何人容易获得他们所需要的精确的音乐,然后在复杂的发展过程中进行解释,从而产生有效的音乐组成,以标准格式制作出有效的音乐。这个系统展示了一种全新的新用途,作为适应性的其他用途。它看起来是完全的新用途。