Autonomous Learning Systems: Concepts, Methodologies, and Applications
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (1 February 2024) | Viewed by 4521
Special Issue Editors
Interests: intelligent computation; knowledge engineering; semantic web; bioinformatics
Interests: optimization and workflow management; machine learning; data analytics; city logistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Autonomous learning systems at the forefront of machine learning and artificial intelligence advancements. These systems, including but not limited to self-learning algorithms, have the potential to learn and improve their performance over time with minimal supervision. They are increasingly applied across a diverse array of domains, from image recognition and natural language processing to healthcare diagnostics and financial predictions. Despite the significant advancements, numerous research challenges persist in the field of autonomous learning systems. How can we design systems that mitigate the risk of confirmation bias, ensure ethical use given their potential autonomy, and address scalability issues in the face of today's big data era?
The aim of this Special Issue is to provide a dedicated platform for researchers and practitioners to share their latest advancements, insights, and experiences in the development, application, and implications of autonomous learning systems. We encourage contributions addressing innovative concepts, methodologies, real-world applications, and ethical considerations in this exciting and rapidly evolving field.
Dr. Xingsi Xue
Dr. Pei-Wei Tsai
Guest Editors
Manuscript Submission Information
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Keywords
- autonomous learning systems
- artificial intelligence
- machine learning
- self-learning algorithms
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