@inproceedings{c30ed38353ff42048eb9710d559909ce,
title = "Neuro-fuzzy learning of locust's marching in a Swarm",
abstract = "This study deals with the identification of the behavior of an individual in a group of marching locusts, as observed under laboratory conditions. In particular, the study focuses on the intermittent motion (walking initiation and pausing) of the locusts using Adaptive Neuro-Fuzzy Inference System (ANFIS). Several possible fuzzy rules were examined in a trial-and-error approach, before establishing a reliable set of rules. Analysis of this set led to a consequent reduced fuzzy controller. The results of this study serve as a first step towards achieving the long-term goal of understanding how the behavior of an individual locust translates to the collective swarm movement. As part of achieving this goal, we plan on building a locust-like robot and investigating its behavior within a living swarm of locusts. On a more general level, this study demonstrates, for the first time, that ANFIS can be used to support the understanding of biological systems by translating experimental data into meaningful control laws.",
keywords = "ANFIS, Artificial life, Fuzzy control, Locust, Swarm, System identification",
author = "Gil Segal and Amiram Moshaiov and Guy Amichay and Amir Ayali",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Joint Conference on Neural Networks, IJCNN 2016 ; Conference date: 24-07-2016 Through 29-07-2016",
year = "2016",
month = oct,
day = "31",
doi = "10.1109/IJCNN.2016.7727335",
language = "الإنجليزيّة",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1208--1215",
booktitle = "2016 International Joint Conference on Neural Networks, IJCNN 2016",
address = "الولايات المتّحدة",
}