Machine Learning for Context-Aware Decision Making and Autonomous AI Agents
A Special Issue of Applied Sciences (ISSN 2076-3417) belonging to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 March 2027 | Viewed by 1
Editors
Interests: machine learning; decision support systems; granular computing; situation awareness; intelligent optimization; artificial intelligence
Interests: medical decision support; healthcare AI; explainable AI
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in machine learning are transforming decision support systems and AI agents from passive predictive tools into adaptive systems that perceive context, reason under conditions of uncertainty, select actions, and interact with humans and other agents. However, reliable decision making in real-world settings requires more than predictive accuracy: models must integrate heterogeneous information, adapt to changing environments, explain their recommendations, and operate safely when data are limited, noisy, or incomplete.
This Special Issue will collect original research and review articles on machine learning methods that enable context-aware, robust, and human-centered decision making in intelligent agents. We welcome contributions on supervised, self-supervised, and reinforcement learning; learning-augmented optimization; uncertainty modeling and granular computing; multi-agent coordination; neuro-symbolic and knowledge-enhanced approaches; explainable and trustworthy AI; human-in-the-loop decision support; and the evaluation, safety, and governance of agentic systems. Particular attention will be paid to methods validated in realistic applications, including industrial automation, robotics, logistics, healthcare, education, cyber–physical systems, energy, and smart environments.
The Special Issue will connect methodological advances with deployable systems and clarify how machine learning can support decisions that are effective, interpretable, adaptive, and aligned with human goals. Comparative studies, benchmarks, datasets, and systematic reviews are also encouraged.
Dr. Mario Lepore
Dr. Chiara Verdone
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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.
Keywords
- machine learning
- decision support systems
- autonomous AI agents
- reinforcement learning
- multi-agent systems
- context-aware AI
- uncertainty-aware learning
- explainable AI
- human-in-the-loop
- trustworthy AI
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