Automatic composition of music by means of Grammatical Evolution

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in APL Quote Quad, http://dx.doi.org/10.1145/604444.602249Proceedings of the 2002 conference on APL: array processing languages: lore, problems, and applications (Madrid)This work describes how grammatical evolution may be applied to the domain of automatic composition. Our goal is to test this technique as an alternate tool for automatic composition. The AP440 auxiliary processor will be used to play music, thus we shall use a grammar that generates AP440 melodies. Grammar evolution will use fitness functions defined from several well-known single melodies to automatically generate AP440 compositions that are expected to sound like those composed by human musicians.This paper has been sponsored by the Spanish Interdepartmental Commission of Science and Technology (CICYT), project numbers TEL1999-0181 and TIC2001-0685-C02-1

Testing genetic algorithm, recombination strategies and the normalized compression distance for computer-generated music

This is an electronic version of the paper presented at the WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED 2006) held in Madrid (Spain) on 2006This paper analyzes the use of the normalized compression distance as a fitness function for the automatic generation of music by means of genetic algorithms, and tests the effect on performance of several genetic recombination procedures. The minimization of the distance of the generated music to a set of musical guides or targets makes it possible to obtain computer-generated music that reminds the style of a certain human author. In spite of the simplicity of the algorithm, the procedure obtains interesting results. The paper includes some considerations on the use of procedures that improve the performance of heavytailed distribution processes.This work has been sponsored by the Spanish Ministry of Education and Science (MEC), project number TSI2005-08225-C07-06

Optimizing ecology-friendly drawing of plans of buildings by means of grammatical evolution

This is an electronic version of the paper presented at the International Industrial Simulation Conference (ISC 2006), held in Palermo (Italy)We explore the application of grammatical evolution to the automatic generation of plans of building with constraints. A BNF is presented that guarantees the conversion of the genetic code into a well formed geometrical figure or phenotype. The validity of the approach is demonstrated, its limitations are analyzed and new evolutionary techniques are suggested for future work in this area

GenoMus: Representing Procedural Musical Structures with an Encoded Functional Grammar Optimized for Metaprogramming and Machine Learning

We present GenoMus, a new model for artificial musical creativity based on a procedural approach, able to represent compositional techniques behind a musical score. This model aims to build a framework for automatic creativity, that is easily adaptable to other domains beyond music. The core of GenoMus is a functional grammar designed to cover a wide range of styles, integrating traditional and contemporary composing techniques. In its encoded form, both composing methods and music scores are represented as one-dimensional arrays of normalized values. On the other hand, the decoded form of GenoMus grammar is human-readable, allowing for manual editing and the implementation of user-defined processes. Musical procedures (genotypes) are functional trees, able to generate musical scores (phenotypes). Each subprocess uses the same generic functional structure, regardless of the time scale, polyphonic structure, or traditional or algorithmic process being employed. Some works produced with the algorithm have been already published. This highly homogeneous and modular approach simplifies metaprogramming and maximizes search space. Its abstract and compact representation of musical knowledge as pure numeric arrays is optimized for the application of different machine learning paradigms.FEDER/Junta de Andalucia A.TIC.244.UGR20 Spanish GovernmentEuropean Commission PID2021-125537NA-I0

Fitness in Evolutionary Art and Music: A Taxonomy and Future Prospects

This paper is concerned with the idea of fitness in art and music systems that are based on evolutionary computation. A taxonomy is presented of the ways in which fitness is used in such systems, with two dimensions: what the fitness function is applied to, and the basis by which the function is constructed. A large collection of papers are classified using this taxonomy. The paper then discusses a number of ideas that have not been used for fitness evaluation in evolutionary art and which might be valuable in future developments: memory, scaffolding, connotation and web search

Un Framework para la generación automática de ejercicios mediante técnicas de mutación

En este trabajo se describe el diseño e implementación de un entorno que genera ejercicios tipo test de forma automática mediante técnicas de mutación, llamado Wodel-Edu. Wodel-Edu es una extensión de post-procesado para el Lenguaje de Dominio Específico (DSL) Wodel, desarrollado por el grupo MISO, y que proporciona primitivas de alto nivel para mutación de modelos. Para ello, se ha extendido el DSL Wodel con nuevas primitivas de mutación, nuevas estrategias de selección, un registro de las mutaciones aplicadas, un control de la generación de mutantes duplicados, y una comprobación de que los mutantes que se generan son modelos correctos (conformes a su meta-modelo). También se ha dotado a Wodel de un mecanismo extensible que permite registrar distintas acciones de post-procesado sobre los mutantes generados, extensión sobre la que se ha implementado el entorno Wodel-Edu. Wodel-Edu es independiente del dominio, y genera tres formatos diferentes de ejercicios tipo test: el primero, en el que se presentan varios diagramas, y el estudiante ha de decidir cuál es el correcto; el segundo, en el que se presenta un único diagrama, y el estudiante ha de decidir si es correcto, o no; el tercer formato, se presentan una serie de posibles cambios a realizar sobre el diagrama para corregirlo, y el estudiante ha de seleccionar cuáles de estos cambios son correctos. En este trabajo se ha elegido utilizar Wodel-Edu para generar ejercicios de autómatas finitos. Se presenta además una evaluación de la aplicación de ejercicios generada.This work presents the design and development of a framework for the automatic generation of test exercises using mutation techniques, that we call Wodel-Edu. Wodel-Edu is a post-processing extension for the Domain-Specific Language (DSL) Wodel - developed by MISO group - that provides high level primitives for model mutation. We extend the DSL Wodel with new mutation primitives, new selection strategies, a registry of the applied mutations, a duplicated mutant generation control, and a verification that the generated mutants are conforming to the meta-model. We also improve Wodel with an extensible mechanism that allows applying post-processing actions to the generated mutants, and we use this feature to include the Wodel-Edu extension in the Wodel environment. Wodel-Edu is domain independent, and generates three kind of test exercises: the first one, where several diagrams are shown to the student, and he has to choose which one is correct; the second one, where just one diagram is shown to the student, and he has to choose if it is correct or not; and the third kind of exercise, where several changes, that can be applied to the diagram, are presented to the student, and he has to choose which of these changes are correct. In this work, we chose to apply Wodel-Edu to generate finite automata exercises. We also present an evaluation of the generated test application

APL'2002 Madrid Proceedings Automatic composition of music by means of Grammatical Evolution

This work describes how grammatical evolution may be applied to the domain of automatic composition. Our goal is to test this technique as an alternate tool for automatic composition. The AP440 auxiliary processor will be used to play music, thus we shall use a grammar that generates AP440 melodies. Grammar evolution will use fitness functions defined from several well-known single melodies to automatically generate AP440 compositions that are expected to sound like those compose