The CMA Evolution Strategy: A Tutorial
arXiv:1604.00772v21672 citations
Originality Synthesis-oriented
AI Analysis
It provides a tutorial on an optimization method for researchers and practitioners in fields like machine learning and engineering.
The paper introduces the CMA Evolution Strategy, a stochastic method for optimizing non-linear, non-convex functions in continuous domains, focusing on intuitive derivation and motivation.
This tutorial introduces the CMA Evolution Strategy (ES), where CMA stands for Covariance Matrix Adaptation. The CMA-ES is a stochastic, or randomized, method for real-parameter (continuous domain) optimization of non-linear, non-convex functions. We try to motivate and derive the algorithm from intuitive concepts and from requirements of non-linear, non-convex search in continuous domain.