A new multi agent system based on online sequential extreme learning machines and Bayesian Formalism

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2 Citations (Scopus)

Abstract

In this article, a new Multi Agent System based on Online Sequential Extreme Learning Machine (OSELM) neural network and Bayesian Formalism (MAS-OSELM-BF) is introduced. It is an improvement of a single OSELM (single agent) by combined multiple OSELMs (multi agents) with a final decision making module (parent agent). Here, the development of the parent agent is motivated by the Bayesian Formalism. A series of empirical studies to assess the effectiveness of the MAS-OSELM-BF in pattern classification tasks is conducted. The results demonstrated that the MAS-OSELM-BF able to produce good performance as compared with a single OSELM and other method that employed ensemble OSLEM (EOSELM).

Original languageEnglish
Title of host publication2011 International Conference on Networking, Sensing and Control, ICNSC 2011
Pages74-79
Number of pages6
DOIs
Publication statusPublished - 11 Jul 2011
Event2011 International Conference on Networking, Sensing and Control, ICNSC 2011 - Delft, Netherlands
Duration: 11 Apr 201113 Apr 2011

Publication series

Name2011 International Conference on Networking, Sensing and Control, ICNSC 2011

Other

Other2011 International Conference on Networking, Sensing and Control, ICNSC 2011
CountryNetherlands
CityDelft
Period11/04/1113/04/11

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering

Cite this

Yap, K. S. (2011). A new multi agent system based on online sequential extreme learning machines and Bayesian Formalism. In 2011 International Conference on Networking, Sensing and Control, ICNSC 2011 (pp. 74-79). [5874946] (2011 International Conference on Networking, Sensing and Control, ICNSC 2011). https://doi.org/10.1109/ICNSC.2011.5874946