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An Agent-Based Model to Investigate Different Behaviours in a Crowd Simulation

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Bioinspired Optimization Methods and Their Applications (BIOMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13627))

Abstract

This paper presents an agent-based model to evaluate the effects of different behaviours in a crowd simulation. Two different behaviours of agents were considered: collaborative, acting attentively and collaboratively, and defector who, on the other hand, acts individually and recklessly. Many experimental simulations on different complexity scenarios were performed and each outcome indicates how the presence of a percentage of defector agents helps and motivates the collaborative ones to be better and more fruitful. This investigation was carried out considering the (i) number of agents evacuated, (ii) exit times and (iii) path costs as evaluation metrics.

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Notes

  1. 1.

    The time unit used that corresponds to a single movement of all agents.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125, Catania, Italy

    Carolina Crespi, Georgia Fargetta, Mario Pavone & Rocco A. Scollo

Authors
  1. Carolina Crespi
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  2. Georgia Fargetta
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  3. Mario Pavone
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  4. Rocco A. Scollo
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Corresponding author

Correspondence to Mario Pavone .

Editor information

Editors and Affiliations

  1. University of Maribor, Maribor, Slovenia

    Marjan Mernik

  2. Jožef Stefan Institute, Ljubljana, Slovenia

    Tome Eftimov

  3. University of Maribor, Maribor, Slovenia

    Matej Črepinšek

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Crespi, C., Fargetta, G., Pavone, M., Scollo, R.A. (2022). An Agent-Based Model to Investigate Different Behaviours in a Crowd Simulation. In: Mernik, M., Eftimov, T., Črepinšek, M. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2022. Lecture Notes in Computer Science, vol 13627. Springer, Cham. https://doi.org/10.1007/978-3-031-21094-5_1

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  • DOI: https://doi.org/10.1007/978-3-031-21094-5_1

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  • Online ISBN: 978-3-031-21094-5

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