We are pleased to invite you to contribute your latest research to a
Special Issue of the journal *Entropy* (ISSN 1099-4300, IF 2.5) entitled:
*"Entropy-Guided Evolutionary Intelligence: Information Dynamics for
Adaptive and Explainable Machine Learning"*
*Overview:* While gradient-based ML has seen massive success, it often
struggles with non-differentiable or dynamic environments. Evolutionary
Artificial Intelligence (EvoAI) provides a biological alternative, but
often lacks principled ways to control uncertainty. This Special Issue
explores how information theory—specifically entropy—can act as a
regulatory principle to govern diversity, convergence, and transparency in
evolutionary processes.
*Scope includes (but is not limited to):*
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Entropy-based fitness and objective functions.
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Information-regulated mutation, recombination, and selection.
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Entropy-driven neuroevolution and hybrid frameworks.
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Uncertainty quantification and explainability (XAI).
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Applications in complex, high-dimensional domains.
*Special Issue Website:*
https://www.mdpi.com/journal/entropy/special_issues/A3361VP55O
We encourage you to submit your original research or comprehensive review
papers. Should you have any questions regarding the suitability of a topic,
please feel free to reach out.
Best regards,
Dr. Diego Oliva
Prof. Dr. Marco Pérez-Cisneros
Guest Editors
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