Publication: A new multi agent system based on online sequential extreme learning machines and Bayesian Formalism
Date
2011
Authors
Yap K.S.
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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). � 2011 IEEE.
Description
Keywords
Bayesian Formalism , Multi Agent System , Online Sequential Extreme Learning Machine , Pattern Classification , Decision making , E-learning , Learning systems , Neural networks , Sequential machines , Bayesian Formalism , Empirical studies , Multi agent , Online Sequential Extreme Learning Machine , Single-agent , Multi agent systems