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

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

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 modu...

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Bibliographic Details
Main Author: Yap K.S.
Other Authors: 24448864400
Format: Conference paper
Published: 2023
Subjects:
Bayesian Formalism
Multi Agent System
Online Sequential Extreme Learning Machine
Pattern Classification
Decision making
E-learning
Learning systems
Neural networks
Sequential machines
Empirical studies
Multi agent
Single-agent
Multi agent systems
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Institution: Universiti Tenaga Nasional
Description
Summary: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). � 2011 IEEE.

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