Abstract: An increasing number of machine learning algorithms are being applied to multi-objective optimization problems (MOPs), yielding promising results. However, many of these algorithms suffer ...
To address these shortcomings, we introduce SymPcNSGA-Testing (Symbolic execution, Path clustering and NSGA-II Testing), a ...
Why AI is becoming ldquo;native rdquo; to 5G/6G networks The evolution from 5G to 6G networks represents a dramatic leap in complexity that fundamentally challenges traditional network management ...
Abstract: Solving constrained multi-objective optimization problems (CMOPs) is a challenging task due to the presence of multiple conflicting objectives and intricate constraints. In order to better ...
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