IJCNN 2020 Special Session
Methods and Applications of Deep Reinforcement Learning to Autonomous Systems
Aim and Scope
Autonomous systems are an important driver of benefit to many companies and organizations. Advances in autonomous technologies affect every part of life, business, industry and education. A class of machine learning methods, namely reinforcement learning (RL), are the backbone of many autonomous systems. Recent developments in deep learning have been integrated into conventional RL, known as deep RL, for building more capable and robust autonomous systems. These autonomous technologies are transforming many industries, most notable is the car industry where autonomous driving systems will lead to huge transformation in the near future. Other businesses have also applied autonomous technologies to stimulate transformation and growth, from the defense and security industries through to the highly-competitive retail sector, supply chains, manufacturing, medical diagnosis systems, remote aged-care and health-care systems, autonomous surgery, cancer treatment planning, in-house robotics, disaster management and smart-grid control.
This special session aims to bring together the recent developments in the theory and application of deep reinforcement learning and autonomous systems. The topics include, but are not limited to:
Advances in deep RL theory
Applications of deep RL-based autonomous technologies in:
o Robotics, surgical robotics, in-house robotics, industrial robots
o Mutli-agent systems, multi-objective problems
o Autonomous vehicles, defense technologies, trusted autonomy
o Smart manufacturing, industrial process, quantum technology
o Vehicle routing problems, transportation, supply chains
o Cybersecurity, smart grid control, financial technology
o IoT applications, mobile edge computing, communication networks
o Image and video processing, natural language processing
o Aged-care systems, medical/health-care systems
Important Dates
Paper Submission: January 30, 2020
Notification of Acceptance: March 15, 2020
Camera Ready Deadline: April 15, 2020
Conference Dates: July 19-24, 2020
Submission Guidelines
This special session will be held in 2020 International Joint Conference on Neural Networks (IJCNN) (wcci2020.org/ijcnn-sessions/), part of 2020 IEEE World Congress on Computational Intelligence (https://wcci2020.org/ ) (Glasgow, Scotland, United Kingdom, July 19-24, 2020).
All papers should be prepared according to the IJCNN 2020 policy and should be submitted electronically using the conference website (https://wcci2020.org/submissions/) .
To submit your paper to this special session, you will use the IJCNN upload link and choose our SPECIAL SESSION "S52. Methods and Applications of Deep Reinforcement Learning to Autonomous Systems" in the research topic list.
All papers accepted and presented at IEEE IJCNN/WCCI 2020 will be included in the conference proceedings published by IEEE Explore, which are typically indexed by EI.
Organizers
Dr. Thanh Thi Nguyen, School of Information Technology, Deakin University, Victoria, Australia.
Email: thanh.nguyen@deakin.edu.au
A/Prof. Vijay Janapa Reddi, John A. Paulson School of Engineering and Applied Sciences, Harvard University, Massachusetts, USA.
Email: vj@eecs.harvard.edu
Prof. Peter W. Eklund, School of Information Technology, Deakin University, Victoria, Australia.
Email: peter.eklund@deakin.edu.au