Graph-Based Mutations for Music Generation

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{kanani:2023:GGP,

• author = "Maziar Kanani and Sean O'Leary and James McDermott",
• title = "{Graph-Based} Mutations for Music Generation",
• booktitle = "Graph-based Genetic Programming",
• year = "2023",
• editor = "Roman Kalkreuth and Thomas Baeck and Dennis G. Wilson and Paul Kaufmann and Leo Francoso Dal Piccol Sotto and Timothy Aktinson",
• pages = "1916--1919",
• address = "Lisbon, Portugal",
• series = "GECCO '23",
• month = "15-19 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, music generation, genetic algorithm, sequitur, graph-based mutation, pathway assembly",
• isbn13 = "9798400701191",
• DOI = "doi:10.1145/3583133.3596318",
• size = "4 pages",
• abstract = "Our study aims to compare the effects of direct mutation and graph-based mutation on representations of music domain. We focus on short tunes from the Irish folk tradition, represented as integer sequences, and use a graph-based representation based on Pathway Assembly (a directed acyclic graph) and the Sequitur algorithm. We define multiple mutation operators to work directly on the sequences or on the graphs, hypothesizing that graph-based mutations will tend to preserve the pattern used per tune, while direct mutation of sequences will tend to destroy patterns, resulting in new generated tunes that are more complex. We perform experiments on a corpus of tunes and apply the mutation operators many times consecutively to analyze their effects.",
• notes = "GECCO-2023 A Recombination of the 32nd International Conference on Genetic Algorithms (ICGA) and the 28th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Maziar Kanani Sean O'Leary James McDermott

Citations