Title :

Combining neural networks and control: potentialities, patterns and perspectives

Author(s) :

Cerf, Sophie [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Rutten, Eric [Auteur]
Laboratoire d'Informatique de Grenoble [LIG]
Control for Autonomic computing systems [CTRL-A]

Conference title :

IFAC 2023 - 22nd World Congress of the International Federation of Automatic Control

Conference organizers(s) :

International Federation of Automatic Control

City :

Yokohama

Country :

Japon

Start date of the conference :

2023-07-09

Book title :

Proceedings of The 22nd World Congress of the International Federation of Automatic Control

Publication date :

2023-07

English keyword(s) :

Machine Learning
Neural Networks
Learning for control
Reinforcement learning and deep learning in control
Machine learning in modelling
prediction
control and automation
Data-driven control

HAL domain(s) :

Sciences de l'ingénieur [physics]/Automatique / Robotique
Informatique [cs]/Intelligence artificielle [cs.AI]

English abstract : [en]

Machine learning tools are widely used for knowledge extraction, modeling, and decision tasks; a range of problems that Control Theory also tackles. Their relations have been largely explored by looking at stochastic control ...
Show more >Machine learning tools are widely used for knowledge extraction, modeling, and decision tasks; a range of problems that Control Theory also tackles. Their relations have been largely explored by looking at stochastic control and Markov Decision Processes, due to the proximity of their formulations. However, novel links between machine learning and deterministic control are emerging; combining both approaches, e.g. by performing identification with learning, or controlling the training process. The recent flourishing literature is vast: there is a need to identify challenges, trends and opportunities on this interface. This survey contributes i) to the compared analysis of both fields. ii) Based on literature review, a categorization of combinations of learning and control is drawn. In the control framework, learning has been used for modeling, controllers tuning or adaptation, generating a controller or as a controller itself, for translating complex objectives, or checking controlled systems. Conversely, in the learning framework, control is used for tuning hyperparameters, selecting or generating training data, as the training or decision-making algorithm itself or to guarantee learning properties. iii) Finally, discussions on the literature open novel promising combinations to be explored, such as control of neural networks' training process.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL