With the development of the Internet of Things and big data technology, today's world has produced more and more complex systems, and generated a large amount of structured, semi-structured, and unstructured data, such as Internet of Things data, industrial data, etc. How to model, analyze, and mine big data according to business scenarios has become a challenging issue for the complex systems. With the continuous development of artificial intelligence technologies such as machine learning and deep learning, this problem has also ushered in new opportunities and challenges. For example, how to combine reinforcement learning-based swarm intelligence technology with industrial control to achieve true artificial intelligence? How to combine swarm intelligence technology with complex systems? These issues have attracted the attention of many scholars in the complex systems. On the one hand, artificial intelligence technologies such as reinforcement learning are a major direction for future scientific and technological development. Once a huge breakthrough occurs, human society will take a big step forward. On the other hand, data is a valuable resource in the new era. Big data technology and data mining technology are the key to discovering its productivity today.

This special session aims to collect the latest original contributions in complex networks, artificial intelligence, etc and offer new ideas, experiences and discussions by experts in this field. We encourage the submission of papers with new theory, analysis, methods, and applications.

This is a special session of the 13th IEEE International Conference on Cyber, Physical and Social Computing (http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php). Please submit your paper via the submission site (TBA) and select the special session of “Big Data for Complex Systems” marked with “CPSComBDCS”.

Accepted conference papers will be published by IEEE (IEEE-DL and EI indexed). Selected papers, after further extensions and revisions, will be recommended to journal special issues. More details at the conference website:
http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php

Potential topics include but are not limited to:

•    Transfer learning for industrial scenarios
•    Multi-agent reinforcement learning
•    Machine learning and data mining in complex networks
•    Complex network reconstruction technology
•    Unsupervised, semi-supervised and supervised learning in industrial big data
•    Machine learning systems and applications in intelligent manufacturing
•    Deep learning and hierarchical models in intelligent manufacturing
•    Preprocessing work related to industrial big data
•    High-Performance Time Series Industrial Big Data Analysis

Session Chairs：
Xuesong Jiang, Qilu University of Technology, jxs@qlu.edu.cn
Ping Jiang, University of Jinan, cse_jiangp@ujn.edu.cn