Towards a Computational Model of Dramatic Tension

One of the approaches to generate narrative consists in modeling narrative in terms of a deep structure, as introduced by narrative theories in the middle of the 20th century. This papers revisits this computational approach, and raises the central issue of dramatic tension: Would it be possible to build a computational model of dramatic tension, where tension could be managed according to the well known ascending/descending dramatic curve? The paper describes a new computational model of narrative, based on a set of structural narrative elements (goals, tasks, obstacles, side-effects), a hierarchical and modular approach, a paradox-based model of dramatic tension and a solution for managing endings. The papers illustrates this theoretical model with a full example

An Emotional Agent for Moral Impairment Rehabilitation in TBI Patients

The ability to identify the emotions of others is a key component of what is known as social cognition. Narratives exploit this mechanism to create an emotional bond with the characters and to maintain the engagement of the audience throughout the story. In this paper, we illustrate a case study in emotion understanding in stories that exploits a computational agent to explore emotion impairment in a group of traumatic brain injured people. The study focuses on moral emotions, aiming to investigate the differences in moral functioning that characterize traumatic brain injured patients. After comparing the understanding of the moral and emotional facets of the agent's behavior in traumatic brain injured patients and in neurologically intact controls, slight–yet meaningful–differences were observed between the two groups. We describe the test methodology and results, highlighting their implications for the design of rehabilitation applications based on virtual agents

Where story and media meet: computer generation of narrative discourse

International audienceStory generation (including interactive narrative) consists of creating a narrative experience on computer by generating narrative events. It requires building an abstract computational model that can generate a variety of narrative events from a limited set of authored content. These models implement a story logic, as they formalize the occurrence of an event in the story according to various algorithms. At the same time, these stories aim to be expressed to an audience using digital media, which requires a medium logic. In this contribution, we look at the relation between story logic and medium logic in the production of mediated narrative discourse. Using the terminology of Russian formalists and a metaphor borrowed from cinema production, we introduce three models of increasing complexity. In the first model, the story logic (fabulist) creates a fabula which is performed by the medium logic (director) to a screenplay then to the screen. In the second model, the story logic (screenwriter) generates a sjuzhet composed of narrative discourse acts that are staged by the medium logic (director). In the third model, the story and medium logics communicate bidirectionally as co-authors of the screenplay in order to render the story optimally.La génération automatique d'histoires consiste à créer une expérience narrative par le calcul de séquences d'événements. Les systèmes de génération automatique d'histoire implémentent une logique narrative qui permet la génération des événements. Ces systèmes prennent également en charge la communication des événements sous une forme médiatisée (son, texte, image) et implémentent donc également une logique médiatique. Dans cette communication, nous examinons les problèmes qui se posent lorsqu'on tente de séparer ces deux logiques, et nous proposons une "lingua fanca" permettant l'échange d'information entre la logique narrative et la logique médiatique

Bridging the Gap Between Hospital and School: Addressing the Academic and Social-Emotional Needs of Students with Chronic Illness

This dissertation in practice examined the literature and a sample of existing programs that addressed the educational and social-emotional challenges of students with chronic illness in order to bridge the gap between hospital discharge and school re-entry. Literature showed that the hospital homebound setting was problematic for chronically ill students due to minimal hours of academic instruction and little interaction with peers. Students with chronic illness were at higher risk for maladaptive behaviors, lower educational attainment, and higher use of social services. Programs created at other facilities to address this problem were visited and reviewed for pertinent information such as funding sources, location, division of responsibility, and relationships with school districts. Those findings were incorporated into a hospital-based learning center model designed to address both the academic and social-emotional needs of elementary students using the Positive Youth Development (PYD) framework. The design process included a focus group of hospital professionals (music therapy, child life, and family-centered care), school district partners (literacy), university partners (art), and parents of chronically ill students. The focus group reviewed the model and provided feedback on the design based on their expertise and modifications were made by the researcher to the design. Webex-Teams, an online meeting platform, was used for stakeholders to review modifications to the physical layout and analyze a proposed sample interdisciplinary session plan. The final model design included five components: literacy, art, music therapy, play, and technology, a physical floorplan, and an interdisciplinary session plan to address the academic and social well-being of chronically ill students that can be replicated at any hospital facility

Personality and Emotion for Virtual Characters in Strong-Story Narrative Planning

Interactive virtual worlds provide an immersive and effective environment for training, education, and entertainment purposes. Virtual characters are an essential part of every interactive narrative. The interaction of rich virtual characters can produce interesting narratives and enhance user experience in virtual environments. I propose models of personality and emotion that are highly domain independent and integrate those models into multi-agent strong-story narrative planning systems. I demonstrate the value of the strong-story properties of the model by generating story conflicts intelligently. My models of emotion and personality enable the narrative generation system to create more opportunities for players to resolve conflicts using certain behavior types. In doing so, the author can encourage the player to adopt and exhibit those behaviors. I conduct multiple human subject and case studies to evaluate these models and show that they enable generating a larger number of stories and character behavior that is preferred and more believable to a human audience

Distinguishing Performance on Tests of Executive Functions Between Those with Depression and Anxiety

Objective: To see if there are differences in executive functions between those diagnosed with Major Depressive Disorder (MDD) and those with Generalized Anxiety Disorder (GAD).Participants and Methods: The data were chosen from a de-identified database at a neuropsychological clinic in South Florida. The sample used was adults diagnosed with MDD (n=75) and GAD (n=71) and who had taken the Halstead Category Test, Trail Making Test, Stroop Test, and the Wisconsin Card Sorting Test. Age (M=32.97, SD=11.75), gender (56.7% female), and race (52.7% White) did not differ between groups. IQ did not differ but education did (MDD=13.41 years, SD=2.45; GAD=15.11 years, SD=2.40), so it was ran as a covariate in the analyses. Six ANCOVAs were run separately with diagnosis being held as the fixed factor and executive function test scores held as dependent variables. Results: The MDD group only performed worse on the Category Test than the GAD group ([1,132]=4.022, p\u3c .05). Even though both WCST scores used were significantly different between the two groups, both analyses failed Levene’s test of Equality of Error Variances, so the data were not interpreted. Conclusions: Due to previous findings that those diagnosed with MDD perform worse on tests of executive function than normal controls (Veiel, 1997), this study wanted to compare executive function performance between those diagnosed with MDD and those with another common psychological disorder. The fact that these two groups only differed on the Category Test shows that there may not be much of a difference in executive function deficits between those with MDD and GAD. That being said, not being able to interpret the scores on the WCST test due to a lack of homogeneity of variance indicates that a larger sample size is needed to compare these two types of patients, as significant differences may be found. The results of this specific study, however, could mean that the Category Test could be used in assisting the diagnosis of a MDD patient

Effects of Diversity and Neuropsychological Performance in an NFL Cohort

Objective: The aim of this study was to examine the effect of ethnicity on neuropsychological test performance by comparing scores of white and black former NFL athletes on each subtest of the WMS. Participants and Methods: Data was derived from a de-identified database in South Florida consisting of 63 former NFL white (n=28, 44.4%) and black (n=35, 55.6%) athletes (Mage= 50.38; SD= 11.57). Participants completed the following subtests of the WMS: Logical Memory I and II, Verbal Paired Associates I and II, and Visual Reproduction I and II. Results: A One-Way ANOVA yielded significant effect between ethnicity and performance on several subtests from the WMS-IV. Black athletes had significantly lower scores compared to white athletes on Logical Memory II: F(1,61) = 4.667, p= .035, Verbal Paired Associates I: F(1,61) = 4.536, p = .037, Verbal Paired Associates: II F(1,61) = 4.677, p = .034, and Visual Reproduction I: F(1,61) = 6.562, p = .013. Conclusions: Results suggest significant differences exist between white and black athletes on neuropsychological test performance, necessitating the need for proper normative samples for each ethnic group. It is possible the differences found can be explained by the psychometric properties of the assessment and possibility of a non-representative sample for minorities, or simply individual differences. Previous literature has found white individuals to outperform African-Americans on verbal and non-verbal cognitive tasks after controlling for socioeconomic and other demographic variables (Manly & Jacobs, 2002). This highlights the need for future investigators to identify cultural factors and evaluate how ethnicity specifically plays a role on neuropsychological test performance. Notably, differences between ethnic groups can have significant implications when evaluating a sample of former athletes for cognitive impairment, as these results suggest retired NFL minorities may be more impaired compared to retired NFL white athletes