作者：DeepRL
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:
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 15, 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.
會議網址(科學上網)：
https://sites.google.com/view/thanh-thi-nguyen/ijcnn-2020-special-session
第11期論文：2019-12-19(3篇，一篇OpennAI,一篇Nvidia)
第10期論文：2019-12-13(8篇)
第9期論文：2019-12-3(3篇)
第8期論文：2019-11-18(5篇)
第7期論文：2019-11-15(6篇)
第6期論文：2019-11-08(2篇)
第5期論文：2019-11-07(5篇，一篇DeepMind發表)
第4期論文：2019-11-05(4篇)
第3期論文：2019-11-04(6篇)
第2期論文：2019-11-03(3篇)
第1期論文：2019-11-02(5篇)