Interactive narratives suffer from the narrative paradox: the tension that exists between providing a coherent narrative experience and allowing a player free reign over what she can manipulate in the environment. Knowing what actions a player in such an environment intends to carry out would help in managing the narrative paradox, since it would allow us to anticipate potential threats to the intended narrative experience and potentially mediate or eliminate them. The process of observing player actions and attempting to come up with an explanation for those actions (i.e. the plan that the player is trying to carry out) is the problem of plan recognition. We adopt the framing of narratives as plans and leverage recent advances that cast plan recognition as planning to develop a symbolic plan recognition system as a proof-of-concept model of a player's reasoning in an interactive narrative environment. In this paper we outline the system architecture, report on performance metrics that demonstrate adequate performance for non-trivial domains, and discuss the implications of treating players as plan recognizers.

In this paper, we present a new modality for intelligent inte r-active narratives within the theatre domain. We discuss the possibilities of using an intelligent agent that serves as a drama manager a nd as an actor that plays a character within the live theatre exper ience. We pose a set of research challenges that arise from our analysi s towards the implementation of such an agent, as well as potential method ologies as a starting point to bridge the gaps between current literatu re and the proposed modality.

The goal of an interactive narrative system is to immerse users in a virtual world such that they believe that they are an integral part of an unfolding story and that their actions can significantly alter the direction 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. The prevalence of storytelling in human culture may be explained by the use of narrative as a cognitive tool for situated understanding (Gerrig 1993). This narrative intelligence -- the ability to organize experience into narrative form -- is central to the cognitive processes employed across a range of experiences, from entertainment to active learning.

The evidence-based analysis of people's navigation and wayfinding behaviour in large-scale built-up environments (e.g., hospitals, airports) encompasses the measurement and qualitative analysis of a range of aspects including people's visual perception in new and familiar surroundings, their decision-making procedures and intentions, the affordances of the environment itself, etc. In our research on large-scale evidence-based qualitative analysis of wayfinding behaviour, we construe visual perception and navigation in built-up environments as a dynamic narrative construction process of movement and exploration driven by situation-dependent goals, guided by visual aids such as signage and landmarks, and influenced by environmental (e.g., presence of other people, time of day, lighting) and personal (e.g., age, physical attributes) factors. We employ a range of sensors for measuring the embodied visuo-locomotive experience of building users: eye-tracking, egocentric gaze analysis, external camera based visual analysis to interpret fine-grained behaviour (e.g., stopping, looking around, interacting with other people), and also manual observations made by human experimenters. Observations are processed, analysed, and integrated in a holistic model of the visuo-locomotive narrative experience at the individual and group level. Our model also combines embodied visual perception analysis with analysis of the structure and layout of the environment (e.g., topology, routes, isovists) computed from available 3D models of the building. In this framework, abstract regions like the visibility space, regions of attention, eye movement clusters, are treated as first class visuo-spatial and iconic objects that can be used for interpreting the visual experience of subjects in a high-level qualitative manner. The final integrated analysis of the wayfinding experience is such that it can even be presented in a virtual reality environment thereby providing an immersive experience (e.g., using tools such as the Oculus Rift) of the qualitative analysis for single participants, as well as for a combined analysis of large group. This capability is especially important for experiments in post-occupancy analysis of building performance. Our construction of indoor wayfinding experience as a form of moving image analysis centralizes the role and influence of perceptual visuo-spatial characteristics and morphological features of the built environment into the discourse on wayfinding research. We will demonstrate the impact of this work with several case-studies, particularly focussing on a large-scale experiment conducted at the New Parkland Hospital in Dallas Texas, USA.

Cinematic, Ambient, Inhabitable Narrative Environments (CAINEs) are conceptual AI-driven interactive story systems combining text, audio, and visual imagery that are scalable and adaptable to a wide range of storytelling needs and interactor inputs. Conceived by at artist outside the AI community, they represent an opportunity to use AI in a nontraditional and immersive narrative fashion that relies not on the goal-based arrangement of story elements, but on the accretion and association of those elements in the minds of interactors. This paper represents the initial phase of the project’s development.

Interactive narrative is a form of storytelling in which users affect a dramatic storyline through actions by assuming the role of characters in a virtual world.This extended abstract outlines the Scheherazade-IF system, which uses crowdsourcing and artificial intelligence to automatically construct text-based interactive narrative experiences.

The workshop was accompanied by an evening Games are unique in that their components event, DAGGER, which drew together local game developers (from the rules and goals of the game to the appearance and academic research projects. Acting both of avatars and their dialogue) must encompass as an exhibition and as an informal gathering, the both functional and aesthetic prerequisites. Artificial DAGGER event allowed attendees to interact directly intelligence usually focuses on the functional quality with a wide variety of game types and technologies, of such game components, for example, ensuring as well as with their developers. As events such that an avatar can traverse a level in minimal time or as DAGGER help bridge the gap between theoretical that AI can win over any human in a strategy game. The papers avatar, or level would appeal to a particular player. of the workshop were published as AAAI Technical The Workshop on AI and Game Aesthetics provided Report WS-13-19.

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.

Interactive narrative systems attempt to tell stories to players capable of changing the direction and/or outcome of the story. Despite the growing importance of multiplayer social experiences in games, little research has focused on multiplayer interactive narrative experiences. We performed a preliminary study to determine how human directors design and execute multiplayer interactive story experiences in online and real world environments. Based on our observations, we developed the Multiplayer Storytelling Engine that manages a story world at the individual and group levels. Our flexible story representation enables human authors to naturally model multiplayer narrative experiences. An intelligent execution algorithm detects when the author's story representation fails to account for player behaviors and automatically generates a branch to restore the story to the authors' original intent, thus balancing authorability against robust multiplayer execution.