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Communication Dans Un Congrès Année : 2019

Hearing the shape of a chemical reactor with a deep network of swarms

Résumé

Biological swarms-from the simplest bacteria to large populations-compute the solution of geometrical problems for their growth and survival. In order to engineer synthetic swarms, it is of interest to understand how biological swarms relate space and time to sense their geometry. Here we propose a swarm architecture that senses the shape of its environment, using agents that form Turing patterns as "sonar", and neural-like layers to process those Turing patterns and find the shape of reactor that generate them.
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Dates et versions

hal-02406947 , version 1 (12-12-2019)

Identifiants

  • HAL Id : hal-02406947 , version 1

Citer

Nicolas Lobato-Dauzier, Leo Cazenille, Nathanaël Aubert-Kato, Alexis Vlandas, Teruo Fujii, et al.. Hearing the shape of a chemical reactor with a deep network of swarms. SWARM 2019: The 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics, Nov 2019, Okinawa, Japan. ⟨hal-02406947⟩
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