The chapter reviews the principles of collective animal behavior, emphasizing the concept of self-organization. Self-organization suggests that simple interactions between individuals can lead to complex adaptive patterns at the group level, similar to physical systems like chemical waves. The author discusses successful examples of self-organization in animal groups, such as ant pheromone trail networks, cockroach aggregation, opera audience applause, and fish school migration. These examples demonstrate how individuals following simple rules can produce coordinated behaviors. However, the complexity of animals as individuals means that not all collective behaviors can be fully explained by simple rules alone. The key to understanding collective behavior lies in identifying the behavioral algorithms followed by individual animals and how information flows between them. The chapter also explores the properties of self-organization, such as positive feedback, response thresholds, and the amplification of random fluctuations. Finally, the author argues for a pragmatic approach to studying collective behavior, focusing on classifying and understanding the principles that govern these behaviors rather than seeking a universal theory.The chapter reviews the principles of collective animal behavior, emphasizing the concept of self-organization. Self-organization suggests that simple interactions between individuals can lead to complex adaptive patterns at the group level, similar to physical systems like chemical waves. The author discusses successful examples of self-organization in animal groups, such as ant pheromone trail networks, cockroach aggregation, opera audience applause, and fish school migration. These examples demonstrate how individuals following simple rules can produce coordinated behaviors. However, the complexity of animals as individuals means that not all collective behaviors can be fully explained by simple rules alone. The key to understanding collective behavior lies in identifying the behavioral algorithms followed by individual animals and how information flows between them. The chapter also explores the properties of self-organization, such as positive feedback, response thresholds, and the amplification of random fluctuations. Finally, the author argues for a pragmatic approach to studying collective behavior, focusing on classifying and understanding the principles that govern these behaviors rather than seeking a universal theory.