2024-03-28T18:12:53Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1350892022-02-07T15:36:25Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134811
2017-09-06T09:16:26Z
urn:hdl:10366/135089
Collaborative Agents for Drilling Optimisation Tasks Using an Unsupervised Connectionist Model
Curiel, Leticia
Herrero Cosío, Álvaro
Corchado Rodríguez, Emilio Santiago
Bravo Díez, Pedro M.
Computer Science
The purpose of this study is the optimization of drilling tasks in the construction of big auto-car storage warehouse. 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.
2017-09-06T09:16:26Z
2017-09-06T09:16:26Z
2005
info:eu-repo/semantics/article
IV International Workshop on Practical Applications of Agents and Multiagent Systems. IWPAAMS'2005.
http://hdl.handle.net/10366/135089
en
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 Unported
Universidad de León