This book provides a standardized, accessible, and usable handbook of algorithmic recipes drawn from Metaheuristics, Biologically Inspired Computation, and Computational Intelligence. The author, Jason Brownlee, addresses the difficulty of implementing AI algorithms by presenting complete, consistent, and centralized descriptions, avoiding the common issues of incomplete or inconsistent information found across various sources. The algorithms are primarily inspired by natural systems, such as evolution, the immune system, and animal foraging behaviors. This reference is designed for a broad audience including research scientists, engineers, students, and amateurs, with each algorithm accompanied by a working Ruby code example.

The book is presented as an encyclopedic reference designed to standardize and clarify the implementation of artificial intelligence algorithms. Its approach focuses on providing complete, consistent, and centralized descriptions, directly addressing the challenges researchers and practitioners face with fragmented or inconsistent information. The inclusion of working code examples in Ruby aims to enhance usability and understanding for a diverse audience, from academic scientists to interested amateurs. The emphasis on algorithms inspired by natural systems suggests a focus on biologically-inspired computational methods.