Clustering Agents for the Evolution of Autonomous Musical Fitness

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Roisin Loughran and Michael O'Neill",
  title =        "Clustering Agents for the Evolution of Autonomous
                 Musical Fitness",
  booktitle =    "6th International Conference on Computational
                 Intelligence in Music, Sound, Art and Design",
  year =         "2017",
  editor =       "Joao Correia and Vic Ciesielski and Antonios Liapis",
  series =       "LNCS",
  volume =       "10198",
  publisher =    "Springer",
  pages =        "160--175",
  address =      "Amsterdam",
  month =        "19-21 " # apr,
  organisation = "Species",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution, Clustering, Self-adaptive system, Autonomous
                 fitness function",
  isbn13 =       "978-3-319-55750-2",
  DOI =          "doi:10.1007/978-3-319-55750-2_11",
  abstract =     "This paper presents a cyclical system that generates
                 autonomous fitness functions or Agents for evolving
                 short melodies. A grammar is employed to create a
                 corpus of melodies, each of which is composed of a
                 number of segments. A population of Agents are evolved
                 to give numerical judgements on the melodies based on
                 the spacing of these segments. The fitness of an
                 individual Agent is calculated in relation to its
                 clustering of the melodies and how much this clustering
                 correlates with the clustering of the entire Agent
                 population. A preparatory run is used to evolve Agents
                 using 30 melodies of known `clustering'. The full run
                 uses these Agents as the initial population in evolving
                 a new best Agent on a separate corpus of melodies of
                 random distance measures. This evolved Agent is then
                 used in combination with the original melody grammar to
                 create a new melody which replaces one of those from
                 the initial random corpus. This results in a complex
                 adaptive system creating new melodies without any human
                 input after initialisation. This paper describes the
                 behaviour of each phase in the system and presents a
                 number of melodies created by the system.",
  notes =        "EvoMusArt2017 held in conjunction with EuroGP'2017,
                 EvoCOP2017 and EvoApplications2017.

Genetic Programming entries for Roisin Loughran Michael O'Neill