The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...

Abstract: Learning to optimize and automated algorithm design are attracting increasing attention, but it is still in its infancy in constrained multiobjective optimization evolutionary algorithms ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. A few public databases provide biological activity data for ...

Abstract: This research proposes a better evolutionary optimization strategy for adapting machine learning models. The strategy balances discovery and exploitation using structured recombination ...

Please provide your email address to receive an email when new articles are posted on . Familial hypercholesterolemia is underdiagnosed and undertreated. A novel machine learning algorithm identified ...

We examine and compare autopoietic systems (biological organisms) and machine learning systems (MLSs) highlighting crucial differences in how causal reasoning emerges and operates. Despite superficial ...

Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...