Uninorm-based neural network and its application for control of mobile robots

Evgeny Kagan, Alexander Rybalov, Hodaya Ziv

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

We suggest the model of recurrent neural network based on the uninorm aggregators and apply it for control of mobile robots. The learning process in the network is governed by the changes of the values neutral elements. The mobile robots in the group are considered as mobile neurons such that their mobility is defined with respect to their internal states. For the suggested model we construct non-monotonic generator function that, however, preserves its monotonicity in the algebraic structure defined by the uninorm and absorbing norm aggregators. The model was verified by numerical simulations and by the trials with the mobile robots.

Original languageEnglish
Title of host publication2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509021529
DOIs
StatePublished - 4 Jan 2017
Event2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 - Eilat, Israel
Duration: 16 Nov 201618 Nov 2016

Publication series

Name2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

Conference

Conference2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Country/TerritoryIsrael
CityEilat
Period16/11/1618/11/16

Keywords

  • Neural network
  • collective behavior
  • mobile robots
  • uninorm

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