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Framing Lifelong Learning as Autonomous Deployment: Tune Once Live Forever

Authors :
Anthony Larcher
Eneko Agirre
Anders Jonsson
University of the Basque Country [Bizkaia] (UPV/EHU)
Universitat Pompeu Fabra [Barcelona] (UPF)
Laboratoire d'Informatique de l'Université du Mans (LIUM)
Le Mans Université (UM)
Source :
International Workshop on Spoken Dialogue Systems Technology, International Workshop on Spoken Dialogue Systems Technology, Apr 2019, Siracusa, Italy, Lecture Notes in Electrical Engineering ISBN: 9789811593222, IWSDS
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

Comunicació presentada a: IWSDS 2019 celebrat del 24 a 26 d'abril de 2019 a Siracusa, Itàlia. Lifelong Learning in the context of Artificial Intelligence is a new paradigm that is still in its infancy. It refers to agents that are able to learn continuously, accumulating the knowledge learned in previous tasks and using it to help future learning. In this position paper we depart from the focus on learning new tasks and instead take a stance from the perspective of the life-cycle of intelligent software. We propose to focus lifelong learning research on autonomous intelligent systems that sustain their performance after deployment in production across time without the need of machine learning experts. This perspective is being applied to three European projects funded under the CHIST-ERA framework on several domains of application. This work has been partially funded by the ALLIES, DELTA and LIHLITH projects supported by the EU ERA-Net CHIST-ERA and the Spanish Research Agency (LIHLITH, PCIN-2017-118; DELTA, PCIN-2017-082).

Details

Language :
English
Database :
OpenAIRE
Journal :
International Workshop on Spoken Dialogue Systems Technology, International Workshop on Spoken Dialogue Systems Technology, Apr 2019, Siracusa, Italy, Lecture Notes in Electrical Engineering ISBN: 9789811593222, IWSDS
Accession number :
edsair.doi.dedup.....78bbf3a7a4b37d1a606901a8d6c00e11