Melomics: A Case-Study of AI in Spain

Traditionally focused on good old-fashioned AI and robotics, the Spanish AI community holds a vigorous computational intelligence substrate. Neuromorphic, evolutionary, or fuzzylike systems have been developed by many research groups in the Spanish computer sciences. It is no surprise, then, that these naturegrounded efforts start to emerge, enriching the AI catalogue of research projects and publications and, eventually, leading to new directions of basic or applied research. In this article, we review the contribution of Melomics in computational creativity.The work on Iamus was partially supported by grants IPT-300000-2010-010 from the Spanish Ministerio de Ciencia e Innovación and TSI-090302-2011-8 from the Spanish Ministerio de Industria, Turismo y Comercio. The first and fourth authors were supported by grant P09-TIC-5123 from the Consejería de Innovación y Ciencia, Junta de Andalucía

Adaptive music: Automated music composition and distribution

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. Music, a form of art broadly present along the human history, is the main field 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, with a genetic encoding of the solutions, which are interpreted in a complex developmental process that leads to music in the standard formats. This bioinspired compositional system has exhibited a high creative power and versatility to produce music of different type, which in many occasions has proven to be indistinguishable from the music made by human composers. The system also has enabled the emergence of a set of completely novel applications: from effective tools to help anyone to easily obtain the precise music they need, to radically new uses like adaptive music for therapy, amusement or many other purposes. It is clear to us that there is much research work yet to do in this field; and that countless and new unimaginable uses will derive from it

Evolutionary design of single-mode microstructured polymer optical fibres using an artificial embryogeny representation

Polymer microstructured optical fibres are a relatively recent development in optical fibre technology, supporting a wide variety of microstructure fibre geometries, when compared to the more commonly used silica. In order to meet the automated design requirements for such complex fibres, a representation was developed which can describe radially symmetric microstructured fibres of different complexities; from simple hexagonal designs with very few holes, to large arrays of hundreds of holes. This representation uses an embryogeny, where the complex phenotype is ‘grown ’ from a simpler genotype, and the resulting complexity is primarily a feature of the reuse of gene elements that describe the microstructure elements. Most importantly, the growth process results in the automatic satisfaction of manufacturing constraints. In conjunction with a multi-objective genetic algorithm, this formed a robust algorithm for the design of microstructured fibres for particular applications of interest. In this paper the algorithm is used to design one of the most common types of microstructured fibres – single-moded fibres. Various types of single-moded designs that have not been encountered in the literature were discovered, identifying new ‘design themes’. One of the designs was subsequently manufactured, the details of which are included

Aportaciones y Aplicaciones de Disciplinas Bioinspiradas a la Creatividad Computacional

¿Puede una computadora presentar comportamientos creativos? Esta compleja cuestión ha despertado un creciente interés en las últimas décadas. Es un hecho evidente que las computadoras han superado la capacidad humana en múltiples dominios. Sin embargo, alcanzar la creatividad humana sigue suponiendo un reto para las computadoras, siendo considerada como un factor clave en el éxito intelectual de los humanos que los diferencia del resto de seres. Esto permite plantear la cuestión acerca de si los humanos poseen un cierto sentido especial, del cual surge la creatividad, que no puede ser transcrito a un algoritmo y por lo tanto, no puede ser implementado por una computadora. Como respuesta a esto, la creatividad computacional surge como un campo dentro de la inteligencia artificial que se encarga del estudio y desarrollo de sistemas hardware y software que sean capaces de exhibir un comportamiento creativo propio del ser humano. Por otra parte, la observación de la naturaleza ha sido una de las principales fuentes de inspiración para la propuesta de novedosas soluciones creativas en diferentes áreas y contextos. En este sentido, dentro de la inteligencia artificial, el paradigma bioinspirado de la computación evolutiva aborda la resolución de problemas mediante la evolución de poblaciones de individuos. La evolución natural representa un ejemplo extremo de proceso creativo ya que durante millones de años, la evolución de los seres vivos ha hecho posible la emergencia de un número inimaginable de diseños biológicos. Por este motivo e inspirados por la evolución natural, los algoritmos evolutivos, una de las técnicas que conforman la computación evolutiva, han sido empleados ampliamente en procesos creativos. Por definición, la creatividad requiere amplias dosis de innovación y diversidad. En el campo de la biología, recientes hipótesis apuntan a que el proceso de desarrollo, en el que una sola célula se transforma en un organismo complejo, es un mecanismo fundamental en el surgimiento de innovación y diversidad en los seres vivos. Por este motivo, el campo de la biología evolutiva del desarrollo (evo-devo) ha emergido para reclamar su incorporación como componente clave en la evolución de una gran diversidad de comportamientos y diseños estructurales innovadores. En el campo de la computación, la biología evolutiva del desarrollo ha inspirado dos disciplinas: el desarrollo artificial, que incorpora el proceso de desarrollo en los algoritmos evolutivos mediante codificación indirecta del esquema genotipo-fenotipo; y la ingeniería embriomórfica, que, imitando el proceso de desarrollo biológico, persigue el desarrollo de morfologías y comportamientos complejos artificiales mediante la agregación descentralizada y la auto-organización de una gran cantidad de pequeños agentes. Entrelazando la compleja cuestión planteada inicialmente sobre la capacidad creativa de las computadoras y la inspiración de la naturaleza como fuente de creatividad e innovación, este trabajo de tesis explora la aplicación de diferentes disciplinas bioinspiradas, concretamente los algoritmos evolutivos, el desarrollo artificial y la ingeniería embriomórfica, de forma individual o combinada para la generación de productos creativos. Para ello se presentan modelos computacionales que actúan de soporte a la creatividad humana, o que exhiben comportamiento creativo de forma independiente, y cuyas soluciones son aplicables en contextos tan diversos como la composición algorítmica, la medicina, la robótica y la animación por computador

Evolutionary Design of Single-Mode Microstructured Polymer Optical Fibres using an Artificial Embryogeny Representation

Polymer microstructured optical fibres are a relatively recent development in optical fibre technology, supporting a wide variety of microstructure fibre geometries, when compared to the more commonly used silica. In order to meet the automated design requirements for such complex fibres, a representation was developed which can describe radially symmetric microstructured fibres of different complexities; from simple hexagonal designs with very few holes, to large arrays of hundreds of holes. This representation uses an embryogeny, where the complex phenotype is ‘grown ’ from a simpler genotype, and the resulting complexity is primarily a feature of reuse of gene elements that describe the microstructure elements. Most importantly, the growth process results in the automatic satisfaction of manufacturing constraints. In conjunction with a multi-objective genetic algorithm, this formed a robust algorithm for the design of microstructured fibres for particular applications of interest. In this paper the algorithm is used to design one of the most common types of microstructured fibres – single-moded fibres. Various types of single-moded designs that have not been encountered in the literature were discovered, identifying new ‘design themes’. One of the designs was subsequently manufactured, the details of which are included