An international team of researchers led by scientists from the Max Planck Institute for Evolutionary Anthropology in Leipzig, working with 15 collaborators around the world, has conducted the most ...

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

Abstract: Differential Evolution (DE) algorithms have shown great promise in solving unmanned aerial vehicle (UAV) path planning problems. However, conventional DE methods often encounter limitations ...

Differential evolution (DE) is a population-based metaheuristic designed to solve continuous global optimization problems with high efficiency and simplicity. Introduced in the mid-1990s, DE ...

This overview traces the evolutionary timeline from the great apes to modern humans, explaining where hominids and hominins split and why that distinction matters. It moves through key branches ...

Abstract: The dendritic neuron model (DNM), inspired by the architecture of biological neurons and renowned for its superior nonlinear information processing capability, presents a promising ...

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

Applying new analytic methods to nearly 16,000 ancient genomes reveals natural selection has acted on hundreds, not dozens, of genes in West Eurasia over the last 10,000 years. More than half of the ...