Artificial intelligence (AI) is almost everywhere due to the rapid development of modern technology and popularity of intelligent devices. While control theory and machine learning techniques as two enabling technologies have shown enormous power in their own right, a rapprochement of them is required to handle nonlinearity, uncertainty and scalability induced by high complexity of modern systems, huge quantity of real-time data, and large scale of agent networks.

Journal of Automation and Intelligence (JAI) aims to provide a platform for researchers and practitioners from both academia and industry to exchange their ideas and present new developments across multiple disciplines relevant to automation and artificial intelligence with particular attention to machine learning.

The JAI welcomes original high-quality contributions associated with theory, design, and applications of control, optimization and machine learning. Potential areas of interest include but are not limited to:

1): control theory and related applications

2): learning driven decision and optimization

3): AI driven automation and autonomy

Editorial Board