Introduction In recent years, the development of evolutionary computation has attracted extensive attention. Based on the Darwinian theorem of “Survival of the Fittest” (Dawkins, 2006; Ma et al., ...

Evolutionary multi-task optimization is an emerging research topic in the field of evolutionary computation. It aims to achieve simultaneous optimization of different tasks by dynamically leveraging ...

The Data Science Lab Simple Numerical Optimization Using an Evolutionary Algorithm with C# Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, ...

Data-driven evolutionary algorithms (DDEAs) have achieved significant success in numerous real-world optimization problems, where exact objective functions and constraint functions do not exist, and ...

The intersection of evolutionary algorithms and reinforcement learning An evolutionary algorithm can serve any number of different purposes, one of which is to help with a continuous-learning model.

Introduction In recent years, the development of evolutionary computation has attracted extensive attention. Based on the Darwinian theorem of “Survival of the Fittest” (Dawkins, 2006; Ma et al., ...