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Two extensions of heterogeneous boid model to avoid metastable patterns

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Abstract

A boid is a simple multiagent model of animal group behavior. Boid agents communicate locally. I studied a heterogeneous boid model comprised of many agents that are divided into several types. While varying interaction among types of agents, this model generates stable patterns with a symmetric interface among different types of agents. As the number of agents increases and as agent clusters grow larger, this model forms a metastable pattern (i.e., a complex of such stable patterns) that is caused by conflict among the local growths of stable patterns. To avoid metastable patterns, I designed two extended heterogeneous boid models: a two-component boid with noise control and a three-component boid with a type transition of agents. In this paper, I examined how these extended models rearrange agents from metastable patterns into stable patterns. These extended models generate stable patterns regardless of the agent number in a shorter time than the original heterogeneous boid model.

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Authors and Affiliations

  1. Biomedical Research Institute, National Institute of Advanced Industry and Technology (AIST), Osaka, Japan

    Mari Nakamura

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  1. Mari Nakamura
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Correspondence to Mari Nakamura.

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This work was presented in part at the 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics (Okinawa, Japan, November 20-22, 2019).

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Nakamura, M. Two extensions of heterogeneous boid model to avoid metastable patterns. Artif Life Robotics 25, 578–587 (2020). https://doi.org/10.1007/s10015-020-00652-0

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  • DOI: https://doi.org/10.1007/s10015-020-00652-0

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