Proposal to add the Samaritan alphabet to the BMP of the UCS

This is a proposal to encode the Samaritan script in the international character encoding standard Unicode. The script was published in Unicode Standard version 5.2 in October 2009. Samaritan is used to write Samaritan Hebrew and Samaritan Aramaic. It is used by small Samaritan communities in Israel and the Palestinian Territories, primarily for religious purposes

Real-Time Storytelling with Events in Virtual Worlds

We present an accessible interactive narrative tool for creating stories among a virtual populace inhabiting a fully-realized 3D virtual world. Our system supports two modalities: assisted authoring where a human storyteller designs stories using a storyboard-like interface called CANVAS, and exploratory authoring where a human author experiences a story as it happens in real-time and makes on-the-fly narrative trajectory changes using a tool called Storycraft. In both cases, our system analyzes the semantic content of the world and the narrative being composed, and provides automated assistance such as completing partially-specified stories with causally complete sequences of intermediate actions. At its core, our system revolves around events -â?? pre-authored multi-actor task sequences describing interactions between groups of actors and props. These events integrate complex animation and interaction tasks with precision control and expose them as atoms of narrative significance to the story direction systems. Events are an accessible tool and conceptual metaphor for assembling narrative arcs, providing a tightly-coupled solution to the problem of converting author intent to real-time animation synthesis. Our system allows simple and straightforward macro- and microscopic control over large numbers of virtual characters with diverse and sophisticated behavior capabilities, and reduces the complicated action space of an interactive narrative by providing analysis and user assistance in the form of semi-automation and recommendation services

The Structural Grammaticalization of the Biblical Hebrew Ethical Dative

This paper offers a structural analysis of the evolution of a grammatical phenomenon in Biblical Hebrew known as the Ethical Dative (ED). My analysis is rooted in the grammaticalization chain proposed by Talmy Givón wherein the Ethical Dative evolves incrementally from other dative forms, accounting for its lopsided distribution across the Bible. Via its similarity to the Personal Dative in Appalachian English, I propose a derivation for the ED whose locus is the specifier of a high Applicative Phrase, allowing us to account for Givón’s progression through the gradual reduction of merge-operations and feature-valuation at that node. My analysis bolsters the notion that the uneven distribution of EDs is indicative of diachronic evolution and not synchronic variation. Moreover, this paper enhances our understanding of a potential grammatical fingerprint within the Hebrew Bible that may aid in discerning authors, time periods, and the broader history of the Bible’s composition and redaction

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

Genetic Adverse Selection: Evidence from Long-Term Care Insurance and Huntington Disease

Individual, personalized genetic information is increasingly available, leading to the possibility of greater adverse selection over time, particularly in individual-payer insurance markets; this selection could impact the viability of these markets. We use data on individuals at risk for Huntington disease (HD), a degenerative neurological disorder with significant effects on morbidity, to estimate adverse selection in long-term care insurance. We find strong evidence of adverse selection: individuals who carry the HD genetic mutation are up to 5 times as likely as the general population to own long-term care insurance. We use these estimates to make predictions about the future of this market as genetic information increases. We argue that even relatively limited increases in genetic information may threaten the viability of private long-term care insurance.

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