Textbook in PDF format This second edition provides an overview of the principal problems, approaches, and challenges in modeling the narrative structure of stories. The book builds upon the prior edition by incorporating an additional focus on generative artificial intelligence and its applications for narratology. The author explains the computational representations of narrative elements, such as characters, events, causality, and time, proposing new methods for representing embedded narratives, fictional entities, tempo, and audience response. The book discusses the rise of generative AI systems, including large language models and transformers. The author explores the current applications of these systems and the extent to which they can be used to automate the cognitive aspects of narrative understanding and generation. Front Matter Introduction Deep Learning and Transformers Introduction to Narratology Plot Basics Time Story Generation Contributions, Extensions and Future Directions Back Matter