A bacterial based distributed gradient descent model for mass scale evacuations

Rashid, Sabrina, Singh, Shashank, Navlakha, Saket, Bar-Joseph, Ziv (May 2019) A bacterial based distributed gradient descent model for mass scale evacuations. Swarm and Evolutionary Computation, 46. pp. 97-103. ISSN 2210-6502

DOI: 10.1016/j.swevo.2019.01.011


Most current methods for distributed agent coordination rely on large messages, complex computations and unique identifiability of communicating agents. To allow for efficient coordination in constrained environments with limited communication and computational resources, we derived a distributed gradient descent (DGD) algorithm based on how bacteria cells interact when searching for food. The method combines the (static) map of each agent with messages received from other agents. Both messages and computations are restricted to a simple vocabulary and are aggregated so no knowledge of the sender is required. In contrast to most prior DGD methods, where the interaction graph is assumed to be static, we allow for dynamic changes in the neighborhood graph for each agent. We prove that the method still correctly converges to a local optimum in such dynamic settings. We tested the usefulness of the method in simulations of mass-scale emergency evacuations in which obstacles are dynamically added to a given environment. We show that our bacterial based model can drastically reduce evacuation times in complex and realistic environments, when compared to prior models.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > computational biology > algorithms
organism description > bacteria
bioinformatics > computational biology
CSHL Authors:
Communities: CSHL labs > Navlakha lab
Depositing User: Matthew Dunn
Date: May 2019
Date Deposited: 06 Nov 2019 16:41
Last Modified: 02 Feb 2024 20:19
Related URLs:
URI: https://repository.cshl.edu/id/eprint/38637

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