Emergent Rhythmic Structures as Cultural Phenomena Driven by Social Pressure in a Society of Artificial Agents

This thesis studies rhythm from an evolutionary computation perspective. Rhythm is the most fundamental dimension of music and can be used as a ground to describe the evolution of music. More specifically, the main goal of the thesis is to investigate how complex rhythmic structures evolve, subject to the cultural transmission between individuals in a society. The study is developed by means of computer modelling and simulations informed by evolutionary computation and artificial life (A-Life). In this process, self-organisation plays a fundamental role. The evolutionary process is steered by the evaluation of rhythmic complexity and by the exposure to rhythmic material. In this thesis, composers and musicologists will find the description of a system named A-Rhythm, which explores the emerged behaviours in a community of artificial autonomous agents that interact in a virtual environment. The interaction between the agents takes the form of imitation games. A set of necessary criteria was established for the construction of a compositional system in which cultural transmission is observed. These criteria allowed the comparison with related work in the field of evolutionary computation and music. In the development of the system, rhythmic representation is discussed. The proposed representation enabled the development of complexity and similarity based measures, and the recombination of rhythms in a creative manner. A-Rhythm produced results in the form of simulation data which were evaluated in terms of the coherence of repertoires of the agents. The data shows how rhythmic sequences are changed and sustained in the population, displaying synchronic and diachronic diversity. Finally, this tool was used as a generative mechanism for composition and several examples are presented.Leverhulme Trus

AI Methods in Algorithmic Composition: A Comprehensive Survey

Algorithmic composition is the partial or total automation of the process of music composition by using computers. Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint programming and evolutionary algorithms. This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence.This study was partially supported by a grant for the MELOMICS project (IPT-300000-2010-010) from the Spanish Ministerio de Ciencia e Innovación, and a grant for the CAUCE project (TSI-090302-2011-8) from the Spanish Ministerio de Industria, Turismo y Comercio. The first author was supported by a grant for the GENEX project (P09-TIC- 5123) from the Consejería de Innovación y Ciencia de Andalucía

THE DEVELOPMENT AND APPLICATION OF COMPUTATIONAL MULTI-AGENT MODELS FOR INVESTIGATING THE CULTURAL TRANSMISSION AND CULTURAL EVOLUTION OF HUMPBACK WHALE SONG

Full version: Access restricted permanently due to 3rd party copyright restrictions. Restriction set on 06.07.2018 by SE, Doctoral CollegeThree different multi-agent models are presented in this thesis, each with a different goal. The first model investigates the possible role migratory routes may have on song evolution and revolution. The second model investigates what social networks could theoretically facilitate song sharing in a population of whales. The third model implements a formal grammar algorithm in order to investigate how the hierarchal structure of the song may affect song evolution. Finally, the thesis attempts to reconnect the models with their origins and discusses how these models could potentially be adapted for composing music. Through the development of these different models, a number of findings are highlighted. The first model reveals that feeding ground sizes may be key locations where song learning from other population may be facilitated. The second model shows that small world social networks facilitate a high degree of agents converging on a single song, similar to what is observed in wild populations. The final model shows that the ability to recognise hierarchy in a sequence coupled with simple production errors, can lead to songs gradually changing over the course of time, while still retaining their hierarchal structure