dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.contributor
Universitat Politècnica de Catalunya. GREC - Grup de Recerca en Enginyeria del Coneixement
dc.contributor.author
Ruiz Vegas, Francisco Javier
dc.contributor.author
Samà Monsonís, Albert
dc.contributor.author
Raya Giner, Cristóbal
dc.contributor.author
Agell Jané, Núria
dc.identifier
Ruiz, F. [et al.]. AoL: Action Learning: A methodology to capture expertise in adjustment tasks. A: Jornadas de ARCA. "Actas de XIV Jornadas de ARCA : Sistemas Cualitativos y sus Aplicaciones en Diagnosis, Robótica e Inteligencia Ambiental". Salou: 2012, p. 95-99.
dc.identifier
978-84-616-2007-4
dc.identifier
https://hdl.handle.net/2117/17652
dc.description.abstract
It is well known that some people can perform a
task with greater precision and accuracy than
others: they are experts. In the past, experts were
interviewed to find out why they have this expertise,
but this was not always completely effective
because often experts "don't know what they
know". In this paper we propose a model of the
process of making decisions performed by experts
in the final adjustment of products task. Based on
this model, we also propose a system based on a
machine learning module that facilitates the capture
of these expert skills. We give an example to illustrate
the process proposed.
dc.description.abstract
Postprint (published version)
dc.format
application/pdf
dc.subject
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
dc.subject
Machine learning
dc.subject
Support vector machines
dc.subject
Decision making
dc.subject
Decisió, Presa de -- Mètodes de simulació
dc.subject
Sistema mixte home-màquina
dc.subject
Aprenentatge automàtic
dc.subject
Intel·ligència artificial
dc.title
AoL: Action Learning: A methodology to capture expertise in adjustment tasks
dc.type
Conference report
