RT info:eu-repo/semantics/conferenceObject
T1 Collaborative agents for drilling optimisation tasks using an unsupervised connectionist model
A1 Curiel Herrera, Leticia Elena
A1 Herrero Cosío, Álvaro
A1 Corchado, Emilio
A1 Bravo Díez, Pedro Miguel
K1 Informática
K1 Computer science
K1 Industria
K1 Industry
K1 Inteligencia artificial
K1 Artificial intelligence
AB The purpose of this study is the optimization of drilling tasks in theconstruction of big auto-carrier storage warehouses. This is carried out byapplying different Artificial Intelligence (AI) techniques: a cooperativeunsupervised connectionist model (focused on the detection of some optimaldrilling conditions) and software agents. These agents can collaborate to savedrilling time and waste by interchanging information about the conditions ofdrill bits and the kind of material to be drilled.
PB Universidad de León. Servicio de Publicaciones
YR 2005
FD 2005
LK http://hdl.handle.net/10259/9394
UL http://hdl.handle.net/10259/9394
LA eng
NO 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
NO This research has been supported by the McyT project TIN2004-07033 and the project BU008B05 of the JCyL.
DS Repositorio Institucional de la Universidad de Burgos
RD 17-jul-2024