Connectionists: Special issue on Intelligent Control and Optimisation - Call for Papers

[Seán McLoone]

Dear colleagues

It is our pleasure to announce a call for papers for a special issue of 
the IFAC/Elsevier Journal Engineering Applications of Artificial 
Intelligence on *'Intelligent Control and Optimisation 
<https://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence/call-for-papers/intelligent-control-and-optimisation>'*.

*Deadline for full paper submission: *31 July 2021

Prospective authors are invited to submit their original unpublished 
manuscripts for consideration for a special issue of the IFAC journal 
Engineering Applications of Artificial Intelligence, organised by the 
IFAC Technical Committee on Computational Intelligence and Control. *The 
**theme of the special issue is Advances in Machine Learning and AI for 
Intelligent Control and Optimisation*.

The constantly increasing availability of data, the rapid expansion in 
computational and storage capacities of IT systems, and algorithmic 
advances in Machine Learning, AI and Intelligent Control, are beginning 
to have a huge impact in many areas of science and engineering.  These 
technologies have the potential to transform many sectors of our 
society, from healthcare to manufacturing. However, many challenges 
remain that are limiting their wide scale adoption, from dealing with 
data quality and volume issues to achieving scalable and robust 
solutions. This special issue invites contributions that address these 
challenges and/or showcase the latest real-world applications and 
enabling algorithmic advancements of Machine Learning and Intelligent 
Control.  Comprehensive tutorial and survey papers are also welcome.

We invite novel contributions that are based on (but not limited to) the 
following topics as they pertain to system identification, intelligent 
control, and optimisation of dynamical systems.

-    Parsimonious and robust machine learning approaches
-    Deep learning, transfer learning and adaption
-    Machine learning approaches for sequence learning tasks
-    Soft computing (Fuzzy logic, Neural Networks, Evolutionary 
Algorithms, …)
-    Reinforcement learning
-    Computer vision

Application areas include autonomous vehicles, robotic systems, 
human-machine collaboration, industry 4.0, smart grids, agriculture, 
environmental systems, biomedical systems and assisted living technologies.

*Prospective authors are asked to notify the guest editors of their 
intention to submit a paper **to the special issu**e* by sending the 
title and a 200-word abstract to Seán McLoone (s.mcloone at qub.ac.uk), to 
confirm the suitability of their contribution for the special issue and 
to receive submission instructions.

Regards

*Guest editors*
Seán McLoone, Queen’s University Belfast, Northern Ireland, 
s.mcloone at qub.ac.uk
Kevin Guelton, University of Reims Champagne Ardenne, France, 
kevin.guelton at univ-reims.fr
Thierry Guerra, University of Valenciennes and Hainaut-Cambresis, 
France, guerra at uphf.fr
Gian Antonio Susto, University of Padova, Italy, gianantonio.susto at unipd.it
Juš Kocijan, Jožef Stefan Institute and University of Nova Gorica, 
Slovenia, jus.kocijan at ijs.si
Diego Romeres, Mitsubishi Electric Research Laboratories, USA, 
romeres at merl.com

-- 
**********************************************************************
Prof. Seán McLoone
Director, Centre for Intelligent Autonomous Manufacturing Systems (i-AMS)
Director, Energy, Power and Intelligent Control Research Centre
School of Electronics, Electrical Engineering and Computer Science
Queen's University Belfast
Ashby Building, Stranmillis Road
Belfast BT9 5AH

Tel:   +44 (0) 28 9097 4125
Email:s.mcloone at qub.ac.uk
Web:http://www.qub.ac.uk/icons2019
Web:http://www.qub.ac.uk/iams
Web:http://www.qub.ac.uk/epic
**********************************************************************

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