Introduction

Chapter 1 briefly introduces the background on LLMs (large language models) and evolutionary computation (EC). More precisely, we provide essential knowledge of metaheuristics, including genetic algorithms (GAs), genetic programming (GP), multi-objective optimization, etc. Next, we explain the basic frameworks of EDAs (estimation of distribution algorithms) and how they are similar to the probabilistic mechanisms of LLMs. Thereafter, we discuss how research on LLMs and metaheuristics relates to each other. Especially, the research on “LLMs as metaheuristics” is the main subject of this book and will be discussed in detail in future chapters.