This chapter presentsSelf-evolving agent a systematic review and methodological exploration of Self-evolving Agents. First, in the overview section, it introduces the research background and driving motivations of self-evolving agents. The chapter then provides an in-depth analysis of their Key Components, including the model, memory, and tools, clarifying the roles of each plays in the evolutionary process. Building on this, the chapter summarizes the key architectures, examining model self-evolution, joint model-memory evolution, joint model-tools evolution, and the joint evolution of model-memory-tools, thereby demonstrating the potential of multi-dimensional collaborative optimization. Furthermore, the chapter outlines the key strategies, which include imitation-based self-evolution and interaction-based self-evolution, highlighting the distinct modes of learning and adaptation within these mechanisms. In the case study section, the chapter presents a complete practical framework for self-evolving agents. Overall, this chapter not only systematizes the theoretical and technical foundations of self-evolving agents but also illustrates their application potential through concrete examples, offering a structured reference framework for future research and practice.