Generative AI and Advanced Computational Methods for Intelligent Systems

Dear Colleagues,

In this era of rapid technological advancements, artificial intelligence (AI) stands as a transformative force shaping the landscape of intelligent systems across various domains. This Special Issue serves as a platform to explore the synergies between conventional AI techniques and the innovative realm of generative AI.

Artificial intelligence has evolved beyond traditional classification and regression approaches, now embracing generative AI, which focuses on making decisions, designs, and insights rather than simply interpreting them. Generative models, such as Generative Adversarial Networks (GANs), diffusion models, and variational autoencoders, open new frontiers for intelligent systems by enabling them to generate novel and diverse outputs, fostering creativity and adaptability.

This Special Issue invites contributions that delve into the intersection of intelligent systems and generative AI and other advanced computational methods, aiming to advance the capabilities of intelligent systems, spanning from smart manufacturing, supply chain management, autonomous vehicles, and energy management. Topics of interest include but are not limited to machine learning, deep learning, computational intelligence, robotics, and autonomous systems. We encourage researchers to explore how these technologies can collectively propel the development of intelligent systems, enhancing their decision making, problem solving, and adaptability.

Join us on this intellectual journey to unravel the potential of artificial intelligence and generative AI in shaping the future of intelligent systems. We anticipate insightful contributions that push the boundaries of innovation and redefine the landscape of intelligent technologies.

Dr. Xingyu Li
Dr. Sihan Huang
Prof. Dr. Baicun Wang
Dr. Xi Gu
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• machine learning
• generative AI
• decision support systems
• autonomous systems
• intelligent automation
• computational intelligence
• natural language processing
• smart manufacturing
• autonomous vehicles
• quality control systems
• supply chain management
• human–robot collaboration
• energy management systems