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A fuzzy-neural multiagent system for optimisation of a roll-mill application

3 Formal Tools Multi-Agent Systems
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 1415)

Abstract

This article presents an industrial application of hybrid system: the development of a fuzzy-neural prototype for optimising a rollmill. The prototype has been developed following an agent-oriented methodology called MAS-CommonKADS. This prototype has the original characteristic of being agent-oriented, i.e. each learning technique has been encapsulated into an agent. This multiagent architecture for hybridisation provides flexibility for testing different hybrid configurations. Moreover, the intelligence of the agents allows them to select the best possible hybrid configuration dynamically, for some applications whereas no best configuration for all the situations has been determined.

Keywords

Hybrid System Fuzzy Rule Multiagent System Rolling Force Rule Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1998

Authors and Affiliations

  1. 1.Dep. de TSC e Ing. Telemática, E.T.S.I. TelecomunicaciónUniversidad de ValladolidValladolidSpain
  2. 2.Dep. de Ingeniería de Sistemas Telemáticos, E.T.S.I. TelecomunicaciónUniversidad Politécnica de MadridMadridSpain

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