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AoL: Action Learning: A methodology to capture expertise in adjustment tasks

Author
Ruiz, F.; Sama, A.; Raya, C.; Agell, N.
Type of activity
Presentation of work at congresses
Name of edition
XIV ARCA days : Qualitative Systems and its Applications in Diagnose, Robotics and Ambient intelligence
Date of publication
2012
Presentation's date
2012-06-26
Book of congress proceedings
Actas de XIV Jornadas de ARCA : Sistemas Cualitativos y sus Aplicaciones en Diagnosis, Robótica e Inteligencia Ambiental
First page
95
Last page
99
Repository
http://hdl.handle.net/2117/17652 Open in new window
URL
http://madeira.lsi.us.es/JARCA12/images/actas%20jarca%202012.pdf Open in new window
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...
Citation
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.
Group of research
CETpD - Technical Research Centre for Dependency Care and Autonomous Living
GREC - Knowledge Engineering Research Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
ISSET - Integrated Smart Sensors and Health Technologies

Participants

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