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A Swarm Grammar-Based Approach to Virtual World Generation

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Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12693))

Abstract

In this work we formulate and propose an extended version of the multi-agent Swarm Grammar (SG) model for the generation of virtual worlds. It unfolds a comparatively small database into a complex world featuring terrain, vegetation and bodies of water. This approach allows for adaptivity of generated assets to their environment, unbounded worlds and interactivity in their generation. In order to evaluate the model, we conducted sensitivity analyses at a local interaction scale. In addition, at a global scale, we investigated two virtual environments, discussing notable interactions, recurring configuration patterns, and obstacles in working with SGs. These analyses showed that SGs can create visually interesting virtual worlds, but require further work in ease of use. Lastly we identified which future extensions might shrink required database sizes.

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Authors and Affiliations

  1. Julius-Maximilians University, Würzburg, Germany

    Yasin Raies & Sebastian von Mammen

Authors
  1. Yasin Raies
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  2. Sebastian von Mammen
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Corresponding author

Correspondence to Yasin Raies .

Editor information

Editors and Affiliations

  1. University of A Coruña, A Coruña, Spain

    Juan Romero

  2. University of Coimbra, Coimbra, Portugal

    Tiago Martins

  3. University of A Coruña, A Coruña, Spain

    Nereida Rodríguez-Fernández

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Raies, Y., von Mammen, S. (2021). A Swarm Grammar-Based Approach to Virtual World Generation. In: Romero, J., Martins, T., Rodríguez-Fernández, N. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2021. Lecture Notes in Computer Science(), vol 12693. Springer, Cham. https://doi.org/10.1007/978-3-030-72914-1_30

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  • DOI: https://doi.org/10.1007/978-3-030-72914-1_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72913-4

  • Online ISBN: 978-3-030-72914-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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