The book "Multi-Hierarchical Representation of Large-Scale Space" offers a comprehensive examination of hierarchical representations in large spatial contexts. It introduces a novel model, the Multi-AH-Graph, which utilizes multiple levels of abstraction to efficiently represent structural information from the environment. This information includes elements such as objects and open spaces, as well as their relationships to one another, such as proximity and similarity. The book highlights the advantages of this multi-layered approach, which adapts better to various tasks, agents, and environments. Additionally, the system CLAUDIA is presented, enabling the automatic construction of multiple abstractions. By optimizing the hierarchies, the efficiency of planning and executing tasks in the respective environment is improved. The content is of interest to both professionals and students in the fields of psychology and computer science, as it illuminates the connection between human information processing and computational models.