My research aims to contribute to research in the narrative authoring domain by using cognitive models in narrative plan generation. These cognitive models determine how actions and events in narrative affect the audience. My research intends to leverage these models in narrative planning and use them to provide intelligent narrative plans that are structured to invoke specific responses from audiences when they experience the narrative. This sort of approach would greatly benefit the enrich growing set of variables of narrative planning. My research is in the nascent field of the computational modeling of narrative, work that seeks to enable computerassisted authoring of stories by modeling the cognitive processes of both author and audience. I intend to extend work on narrative generation that uses planning algorithms to create stories that are consistent and complete (Young 2007). Previous work in narrative planning has been effective at borrowing policy planning and state-space search algorithms from AI in order to generate plot (Riedl and Young 2014). However, the majority of this work focuses on structural properties of a story (e.g., causal consistency (Li et al. 2012), intentionality (Riedl and Young 2010), conflict between characters (Ware et al. 2014)) but does not address the impact that the story has on the cognitive and affective response of its audience (e.g., tension, suspense). The goal of my work is to leverage models of author and audience to address these types of limitations.