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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/9394

    Título
    Collaborative agents for drilling optimisation tasks using an unsupervised connectionist model
    Autor
    Curiel Herrera, Leticia ElenaUBU authority Orcid
    Herrero Cosío, ÁlvaroUBU authority Orcid
    Corchado, EmilioUBU authority Orcid
    Bravo Díez, Pedro MiguelUBU authority Orcid
    Publicado en
    4th International workshop on practical applications of agents and multiagent systems, p. 199-205
    Editorial
    Universidad de León. Servicio de Publicaciones
    Fecha de publicación
    2005
    Descripción
    Trabajo presentado en: 4th International Workshop on Practical Applications of Agents and Multiagent Systems (IWPAAMS), realizado el 20 y 21 de octubre de 2005, en León
    Abstract
    The purpose of this study is the optimization of drilling tasks in the construction of big auto-carrier storage warehouses. This is carried out by applying different Artificial Intelligence (AI) techniques: a cooperative unsupervised connectionist model (focused on the detection of some optimal drilling conditions) and software agents. These agents can collaborate to save drilling time and waste by interchanging information about the conditions of drill bits and the kind of material to be drilled.
    Materia
    Informática
    Computer science
    Industria
    Industry
    Inteligencia artificial
    Artificial intelligence
    URI
    http://hdl.handle.net/10259/9394
    Versión del editor
    https://dialnet.unirioja.es/servlet/libro?codigo=959658
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    Curiel-Collaborative_Agents_Drilling_Optimisation_2005.pdf
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    Universidad de Burgos

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