Researchers have reformulated multi-class classification as a many-objective problem in which each class is a separate goal, ...

TSD, a three-population, two-stage evolutionary algorithm that significantly outperforms seven state-of-the-art methods on ...

Evolutionary reinforcement learning is an exciting frontier in machine learning, combining the strengths of two distinct approaches: reinforcement learning and evolutionary computation. In ...

A team of researchers led by Yumin Dong of Chongqing Normal University has developed a novel method to optimize parametric quantum circuits, a critical component of variational quantum algorithms. The ...

Evolutionary computation encompasses a family of population-based metaheuristic methods inspired by natural evolution. Candidate solutions, encoded as genotypes, undergo iterative cycles of variation ...