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Artificial Intelligence Review

, Volume 46, Issue 2, pp 225–266 | Cite as

Influence of social network on method musical composition

  • Roman Anselmo Mora-GutiérrezEmail author
  • Eric Alfredo Rincón-García
  • Antonin Ponsich
  • Javier Ramírez-Rodríguez
  • Iris Iddaly Méndez-Gurrola
Article

Abstract

The method of musical composition (MMC) is a metaheuristic based on sociocultural creativity systems. Within the MMC, models of social influence and social learning are used and integrated in a social network, which is composed of a set of individuals with links between them and involves a set of interaction rules. In this paper, a comparative study on the performance of the MMC with different network structures is proposed. Sixteen benchmark nonlinear optimization problems are solved, taking into account nine social topologies, which are: (a) linear, (b) tree, (c) star, (d) ring, (e) platoons, (f) von Neumann, (g) full connection, (h) random and (i) small world. In addition, the update of each topology structure was tested according to four different strategies: one static, two dynamic and one self-adaptive states. An exhaustive statistical analysis of the obtained numerical results indicates that the social dynamics has no significant impact on the MMC’s behavior. However, the topology structures can be classified into groups that consistently influence the performance level of the MMC. More precisely, a structure characterized by a low value of its mean number of neighbors and a rather fast information transfer process (star topology) performs in a radically opposite way as structures where each agent has many neighbors (random and complete topologies). These observations allow to provide some guidelines for the selection of a network topology used within a social algorithm.

Keywords

Network topologies Multi-agent search systems Non-linear optimization 

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Roman Anselmo Mora-Gutiérrez
    • 1
    Email author
  • Eric Alfredo Rincón-García
    • 1
  • Antonin Ponsich
    • 1
  • Javier Ramírez-Rodríguez
    • 1
  • Iris Iddaly Méndez-Gurrola
    • 1
  1. 1.Departamento de SistemasUniversidad Autónoma MetropolitanaMexicoMexico

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