Measuring the quality of plot is a desirable feature for computational narrative systems.One of the notions of plot quality used in narrative theory is called tellability, which can be derived from certain structural properties, namely the types of events present and the way they are connected.These structures include not only actualized events, but also take into account virtual plans and the affective valencies of events.The present paper introduces Marie-Laure Ryan's tellability principles and suggests to computationally model them using an affective multi-agent simulation system.It discusses how such an approach implies a broader understanding of plot than commonly assumed and analysis several existing narrative systems under these considerations.Furthermore, it introduces a plot-graph formalism that allows the computational representation and analysis of the extended plot understanding.An approach to automatically generating the plot-graph is suggested in the context of the introduced multi-agent simulation system.

This paper presents an approach to automatically extracting and representing narrative information from stories written in natural language. Specifically, we present our results in extracting story graphs, a formalism that captures the entities (e.g., characters, props, locations) and their interactions in a story. The long-term goal of this research is to automatically extract this narrative information in order to use it in computational narrative systems such as story generators or interactive fiction systems. Our approach combines narrative domain knowledge and off-the-shelf natural language processing (NLP) tools into a machine learning framework to build story graphs by automatically identifying entities, actions, and narrative roles. We report the performance of our fully automated system in a corpus of 21 stories and provide examples of the extracted story graphs and their uses in computational narrative systems.

Interactive narrative systems produce branching story experiences for a human user using an interactive world. A class of interactive narrative systems, called strong story systems, manage a user's experience by manipulating the interactive world and its characters according to a formal story model. In these systems, a human user may place the world into a state such that the formal story model can no longer control interaction. One solution to this problem, called intervention, is to exchange the undesirable outcomes of a player's action for a set that do not violate the story model. However, the player may become aware that their intended action is being intervened against by a context-sensitive, meta-narrative process. In this paper we describe a method of ensuring game world alibis for interventions through domain modification of world mechanics.

This paper presents an interactive narrative framework we have designed for games that promote health behavior change. The framework aims to address two key issues: player engagement with the game, and player adherence to the health behavior change-related homework they receive in the game. In this paper, we describe our narrative system that tackles these issues and a prototype game that promotes physical activity in which our narrative system is integrated.

Interactive narrative is a form of digital interactive experience in which users create or influence a dramatic storyline through their actions. The goal of an interactive narrative system is to immerse the user in a virtual world such that he or she believes that they are an integral part of an unfolding story and that their actions can significantly alter the direction and/or outcome of the story.In this article we review the ways in which artificial intelligence can be brought to bear on the creation of interactive narrative systems. We lay out the landscape of about 20 years of interactive narrative research and explore the successes as well as open research questions pertaining to the novel use of computational narrative intelligence in the pursuit of entertainment, education, and training.

Building complete interactive narrative systems is hard. Building systems that are satisfying for naïve users is especially hard since small deficiencies in component technologies can easily destroy the experience for a user. In this paper I argue that we can ameliorate some of these technical limitations through careful choice of genre and style, and discuss a number of properties of farce that make it a particularly attractive choice. Then I will describe work in progress on Punch and Judy AI Playset, a system that allows users to explore possible narratives in the Punch and Judy story world.