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Memory Induced Aggregation in Collective Foraging

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Swarm Intelligence (ANTS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12421))

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Abstract

Foraging for resources is critical to the survival of many animal species. When resources are scarce, individuals can benefit from interactions, effectively parallelizing the search process. Moreover, communication between conspecifics can result in aggregation around salient patches, rich in resources. However, individual foragers often have short communication ranges relative to the scale of the environment. Hence, formation of a global, collective memory is difficult since information transfer between foragers is suppressed. Despite this limitation, individual motion can enhance information transfer, and thus enable formation of a collective memory. In this work, we study the effect of individual motion on the aggregation characteristics of a collective system of foragers during collective foraging. Using an agent-based model, we show that aggregation around salient patches can occur through formation of collective memory realized through local interactions and global displacement using Lévy walks. We show that the Lévy parameter that defines individual dynamics, and a decision parameter that defines the balance between exploration and exploitation, greatly influences the macroscopic aggregation characteristics. When individuals prefer exploration, global aggregation around a single patch occurs when explorative bouts are relatively short. In contrast, when individuals tend to exploit the collective memory, explorative bouts should be longer for global aggregation to occur. Local aggregation emerges when exploration is suppressed, regardless of the value of the decision parameter.

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Notes

  1. 1.

    The masses of each forager are equal and hence can be omitted.

  2. 2.

    Computation of this expected value assumes a uniform distribution with the center of mass located at the center of the environment \(\mathbf {c} = (L/2,L/2)\).

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Acknowledgments

The authors would like to thank Ilja Rausch for useful discussions and providing invaluable resources specific to the domain.

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Authors and Affiliations

  1. Department of Information Technology–IDLab, Ghent University–imec, Ghent, Belgium

    Johannes Nauta, Pieter Simoens & Yara Khaluf

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  1. Johannes Nauta
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Corresponding author

Correspondence to Johannes Nauta .

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Editors and Affiliations

  1. Université Libre de Bruxelles, Brussels, Belgium

    Marco Dorigo

  2. Université Libre de Bruxelles, Brussels, Belgium

    Thomas Stützle

  3. Universitat Politècnica de Catalunya, Barcelona, Spain

    Maria J. Blesa

  4. Artificial Intelligence Research Institute, Bellaterra, Spain

    Christian Blum

  5. University of Lübeck, Lübeck, Germany

    Heiko Hamann

  6. Université Libre de Bruxelles, Brussels, Belgium

    Mary Katherine Heinrich

  7. Université Libre de Bruxelles, Brussels, Belgium

    Volker Strobel

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Nauta, J., Simoens, P., Khaluf, Y. (2020). Memory Induced Aggregation in Collective Foraging. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2020. Lecture Notes in Computer Science(), vol 12421. Springer, Cham. https://doi.org/10.1007/978-3-030-60376-2_14

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