An Event-Centric Planning Approach for Dynamic Real-Time Narrative

In this paper, we propose an event-centric planning framework for directing interactive narratives in complex 3D environments populated by virtual humans. Events facilitate precise authorial control over complex interactions involving groups of actors and objects, while planning allows the simulation of causally consistent character actions that conform to an overarching global narrative. Events are defined by preconditions, postconditions, costs, and a centralized behavior structure that simultaneously manages multiple participating actors and objects. By planning in the space of events rather than in the space of individual character capabilities, we allow virtual actors to exhibit a rich repertoire of individual actions without causing combinatorial growth in the planning branching factor. Our system produces long, cohesive narratives at interactive rates, allowing a user to take part in a dynamic story that, despite intervention, conforms to an authored structure and accomplishes a predetermined goal

Selecting Agents for Narrative Roles

We present ongoing work on a system that accommodates player agency in a digital narrative with an external plot. We focus on key events that should occur in that storyline for dramatic effect, but do not explicitly specify the characters that should fill the roles needed for those events. Instead, we define them abstractly, with characteristics that the selected characters should have (including previous events they should have completed for eligibility), and rely on a Director construct to populate those roles from agents in the selection pool that fit those criteria. Agents begin as largely homogeneous, primordial entities that accumulate data and narrative value from the events in which they participate. This creates an environment that differentiates characters by the actions they perform, conferring worth onto characters that become important to the player based on their direct involvement in the plot. The focus, then, is on defining a priori the what of the narrative, while leaving it to the Director construct to decide at runtime exactly who among a distributed pool of agents carries it out

ADAPT: The Agent Development and Prototyping Testbed

We present ADAPT, a flexible platform for designing and authoring functional, purposeful human characters in a rich virtual environment. Our framework incorporates character animation, navigation, and behavior with modular interchangeable components to produce narrative scenes. Our animation system provides locomotion, reaching, gaze tracking, gesturing, sitting, and reactions to external physical forces, and can easily be extended with more functionality due to a decoupled, modular structure. Additionally, our navigation component allows characters to maneuver through a complex environment with predictive steering for dynamic obstacle avoidance. Finally, our behavior framework allows a user to fully leverage a character’s animation and navigation capabilities when authoring both individual decision-making and complex interactions between actors using a centralized, event-driven model

Planning Approaches to Constraint-Aware Navigation in Dynamic Environments

Path planning is a fundamental problem in many areas, ranging from robotics and artificial intelligence to computer graphics and animation. Although there is extensive literature for computing optimal, collision-free paths, there is relatively little work that explores the satisfaction of spatial constraints between objects and agents at the global navigation layer. This paper presents a planning framework that satisfies multiple spatial constraints imposed on the path. The type of constraints specified can include staying behind a building, walking along walls, or avoiding the line of sight of patrolling agents. We introduce two hybrid environment representations that balance computational efficiency and search space density to provide a minimal, yet sufficient, discretization of the search graph for constraint-aware navigation. An extended anytime dynamic planner is used to compute constraint-aware paths, while efficiently repairing solutions to account for varying dynamic constraints or an updating world model. We demonstrate the benefits of our method on challenging navigation problems in complex environments for dynamic agents using combinations of hard and soft, attracting and repelling constraints, defined by both static obstacles and moving obstacles

Intelligent Camera Control Using Behavior Trees

Automatic camera systems produce very basic animations for virtual worlds. Users often view environments through two types of cameras: a camera that they control manually, or a very basic automatic camera that follows their character, minimizing occlusions. Real cinematography features much more variety producing more robust stories. Cameras shoot establishing shots, close-ups, tracking shots, and bird’s eye views to enrich a narrative. Camera techniques such as zoom, focus, and depth of field contribute to framing a particular shot. We present an intelligent camera system that automatically positions, pans, tilts, zooms, and tracks events occurring in real-time while obeying traditional standards of cinematography. We design behavior trees that describe how a single intelligent camera might behave from low-level narrative elements assigned by “smart events”. Camera actions are formed by hierarchically arranging behavior sub-trees encapsulating nodes that control specific camera semantics. This approach is more modular and particularly reusable for quickly creating complex camera styles and transitions rather then focusing only on visibility. Additionally, our user interface allows a director to provide further camera instructions, such as prioritizing one event over another, drawing a path for the camera to follow, and adjusting camera settings on the fly.We demonstrate our method by placing multiple intelligent cameras in a complicated world with several events and storylines, and illustrate how to produce a well-shot “documentary” of the events constructed in real-time

Animating Synthetic Dyadic Conversations With Variations Based on Context and Agent Attributes

Conversations between two people are ubiquitous in many inhabited contexts. The kinds of conversations that occur depend on several factors, including the time, the location of the participating agents, the spatial relationship between the agents, and the type of conversation in which they are engaged. The statistical distribution of dyadic conversations among a population of agents will therefore depend on these factors. In addition, the conversation types, flow, and duration will depend on agent attributes such as interpersonal relationships, emotional state, personal priorities, and socio-cultural proxemics. We present a framework for distributing conversations among virtual embodied agents in a real-time simulation. To avoid generating actual language dialogues, we express variations in the conversational flow by using behavior trees implementing a set of conversation archetypes. The flow of these behavior trees depends in part on the agents’ attributes and progresses based on parametrically estimated transitional probabilities. With the participating agents’ state, a ‘smart event’ model steers the interchange to different possible outcomes as it executes. Example behavior trees are developed for two conversation archetypes: buyer–seller negotiations and simple asking–answering; the model can be readily extended to others. Because the conversation archetype is known to participating agents, they can animate their gestures appropriate to their conversational state. The resulting animated conversations demonstrate reasonable variety and variability within the environmental context. Copyright © 2012 John Wiley & Sons, Ltd

Dose-dependent improvement of myoclonic hyperkinesia due to Valproic acid in eight Huntington's Disease patients: a case series

BACKGROUND: Chorea in Huntington's Disease (HD) is usually treated with antidopaminergic neuroleptics like haloperidol, olanzapine and tiaprid or dopamine depleting drugs like tetrabenazine. Some patients with hyperkinesia, however, react to treatment with antidopaminergic drugs by developing extrapyramidal side effects. In earlier studies valproic acid showed no beneficial effect on involuntary choreatic movements. Myoclonus is rare in HD and is often overseen or misdiagnosed as chorea. METHODS: In this report, we present eight patients whose main symptom is myoclonic hyperkinesia. All patients were treated with valproic acid and scored by using the Unified Huntington's Disease Rating Scale (UHDRS) motor score before and after treatment. In addition to this, two patients agreed to be videotaped. RESULTS: In seven patients myoclonus and, therefore the UHDRS motor score improved in a dose dependent manner. In three of these patients antidopaminergic medication could be reduced. CONCLUSION: In the rare subgroup of HD patients suffering from myoclonic hyperkinesia, valproic acid is a possible alternative treatment

Huntington's disease: a clinical review

Huntington disease (HD) is a rare neurodegenerative disorder of the central nervous system characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. Prevalence in the Caucasian population is estimated at 1/10,000-1/20,000. Mean age at onset of symptoms is 30-50 years. In some cases symptoms start before the age of 20 years with behavior disturbances and learning difficulties at school (Juvenile Huntington's disease; JHD). The classic sign is chorea that gradually spreads to all muscles. All psychomotor processes become severely retarded. Patients experience psychiatric symptoms and cognitive decline. HD is an autosomal dominant inherited disease caused by an elongated CAG repeat (36 repeats or more) on the short arm of chromosome 4p16.3 in the Huntingtine gene. The longer the CAG repeat, the earlier the onset of disease. In cases of JHD the repeat often exceeds 55. Diagnosis is based on clinical symptoms and signs in an individual with a parent with proven HD, and is confirmed by DNA determination. Pre-manifest diagnosis should only be performed by multidisciplinary teams in healthy at-risk adult individuals who want to know whether they carry the mutation or not. Differential diagnoses include other causes of chorea including general internal disorders or iatrogenic disorders. Phenocopies (clinically diagnosed cases of HD without the genetic mutation) are observed. Prenatal diagnosis is possible by chorionic villus sampling or amniocentesis. Preimplantation diagnosis with in vitro fertilization is offered in several countries. There is no cure. Management should be multidisciplinary and is based on treating symptoms with a view to improving quality of life. Chorea is treated with dopamine receptor blocking or depleting agents. Medication and non-medical care for depression and aggressive behavior may be required. The progression of the disease leads to a complete dependency in daily life, which results in patients requiring full-time care, and finally death. The most common cause of death is pneumonia, followed by suicide

WHODAS 2.0 in prodromal Huntington disease : measures of functioning in neuropsychiatric disease

We thank the PREDICT-HD sites, the study participants, the National Research Roster for Huntington Disease Patients and Families, the Huntington’s Disease Society of America and the Huntington Study Group. This research was supported by the National Center for Advancing Translational Sciences, and the National Institutes of Health (NIH), through Grant 2 UL1 TR000442-06. This research is supported by the National Institutes of Health, National Institute of Neurological Disorders and Stroke (NS040068), CHDI Foundation, Inc (A3917), Cognitive and Functional Brain Changes in Preclinical Huntington’s Disease (HD) (5R01NS054893), 4D Shape Analysis for Modeling Spatiotemporal Change Trajectories in Huntington’s (1U01NS082086), Functional Connectivity in Pre-manifest Huntington’s Disease (1U01NS082083), and Basal Ganglia Shape Analysis and Circuitry in Huntington’s Disease (1U01NS082085).Peer reviewedPublisher PD