Narratologists, anthropologists, psychologists and artificial intelligence researchers suggest that narrative intelligence (the generation and comprehension of stories) depends on competencies that distinguish us from our primate relatives. Stories play a foundational role in our cognition and are ubiquitous: They can serve as a target of interpretation and as a framework to understand the world around us. Driven by the recognition that the study of narrative is a worthwhile endeavor and that computational modeling is well suited to precisely understand this complex human phenomenon, my research focuses on creating computational-cognitive models of narrative. In particular, I characterize the cognitive processes at play in interactive narrative contexts (i.e. video games) that require a player to understand a narrative setting as well as her role and options for action within it. Key to this understanding is memory performance, which plays an important role in a person’s projection of a fictional world by shaping expectations for the future development of a narrative. In essence, working memory guides the prediction of future human action and I model it to understand what I define as “narrative affordances” – courses of action that a game player can imagine as part of a story that completes her current story experience. In this talk, I will cover the context and development of my computational model of narrative memory and outline the remaining work that I expect to complete over the coming year to validate it as a plausible model of narrative memory performance. I also will focus on the model's capability to guide the computational generation of narrative that cares to achieve a specific mental configuration in the mind of a human consumer. Finally, I will highlight some exciting future directions that leverage high-performance computing to explore narrative intelligence cognitive modeling in dynamic and stochastic environments.