The book "Extending the Scalability of Linkage Learning Genetic Algorithms" by Ying-ping Chen offers a comprehensive analysis and enhancement of the performance of genetic algorithms (GAs), particularly regarding the learning of genetic linkages. Genetic algorithms are proven search techniques based on evolutionary principles and are used in many disciplines for problem-solving. The work highlights the challenges associated with the linkage problem and introduces the Linkage Learning Genetic Algorithm (LLGA), which has been specifically designed to address these challenges. Despite its superiority in poorly scaled problems, the LLGA shows weaknesses in uniformly scaled problems, underscoring the need for a deeper investigation and improvement of its mechanisms. The book begins with an overview of existing techniques in genetic linkage learning and describes the methods developed to enhance LLGA performance in practice, including the use of promoters and the development of a model for convergence time.