Jan M. Allbeck

Dynamically altering agent behaviors using natural language instructions

Smart avatars are virtual human representations controlled by real people. Given instructions interactively, smart avatars can act as autonomous or reactive agents. During a real-time simulation, a user should be able to dynamically refine his or her avatar’s behavior in reaction to simulated stimuli without having to undertake a lengthy off-line programming session. In this paper, we introduce an architecture, which allows users to input immediate or persistent instructions using natural language and see the agents’ resulting behavioral changes in the graphical output of the simulation.

Creating crowd variation with the OCEAN personality model

Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or naive user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (High-Density Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors.

How the Ocean Personality Model Affects the Perception of Crowds

This approach extends the HiDAC (High-Density Autonomous Crowds) system by providing each agent with a personality model based on the Ocean (openness, conscientiousness, extroversion, agreeableness, and neuroticism) personality model. Each personality trait has an associated nominal behavior. Specifying an agents personality leads to an automation of low-level parameter tuning.

Evaluation of American Sign Language Generation by Native ASL Signers

There are many important factors in the design of evaluation studies for systems that generate animations of American Sign Language (ASL) sentences, and techniques for evaluating natural language generation of written texts are not easily adapted to ASL. When conducting user-based evaluations, several cultural and linguistic characteristics of members of the American Deaf community must be taken into account so as to ensure the accuracy of evaluations involving these users. This article describes an implementation and user-based evaluation (by native ASL signers) of a prototype ASL natural language generation system that produces sentences containing classifier predicates, which are frequent and complex spatial phenomena that previous ASL generators have not produced. Native signers preferred the systems output to Signed English animations -- scoring it higher in grammaticality, understandability, and naturalness of movement. They were also more successful at a comprehension task after viewing the systems classifier predicate animations.

Smart events and primed agents

We describe a new organization for virtual human responses to dynamically occurring events. In our approach behavioral responses are enumerated in the representation of the event itself. These Smart Events inform an agent of plausible actions to undertake. We additionally introduce the notion of agent priming, which is based on psychological concepts and further restricts and simplifies action choice. Priming facilitates multi-dimensional agents and in combination with Smart Events results in reasonable, contextual action selection without requiring complex reasoning engines or decision trees. This scheme burdens events with possible behavioral outcomes, reducing agent computation to evaluation of a case expression and (possibly) a probabilistic choice. We demonstrate this approach in a small group scenario of agents reacting to a fire emergency.

Evaluating American Sign Language generation through the participation of native ASL signers

We discuss important factors in the design of evaluation studies for systems that generate animations of American Sign Language (ASL) sentences. In particular, we outline how some cultural and linguistic characteristics of members of the American Deaf community must be taken into account so as to ensure the accuracy of evaluations involving these users. Finally, we describe our implementation and user-based evaluation (by native ASL signers) of a prototype ASL generator to produce sentences containing classifier predicates, frequent and complex spatial phenomena that previous ASL generators have not produced.

Virtual Crowds: Steps Toward Behavioral Realism

This volume presents novel computational models for representing digital humans and their interactions with other virtual characters and meaningful environments. In this context, we describe efficient algorithms to animate, control, and author human-like agents having their own set of unique capabilities, personalities, and desires. We begin with the lowest level of footstep determination to steer agents in collision-free paths. Steering choices are controlled by navigation in complex environments, including multi-domain planning with dynamically changing situations. Virtual agents are given perceptual capabilities analogous to those of real people, including sound perception, multi-sense attention, and understanding of environment semantics which affect their behavior choices. The roles and impacts of individual attributes, such as memory and personality are explored. The animation challenges of integrating a number of simultaneous behavior and movement demands on an agent are addressed through an open source software system. Finally, the creation of stories and narratives with groups of agents subject to planning and environmental constraints culminates the presentation.

ACUMEN: amplifying control and understanding of multiple entities

In virtual environments, the control of numerous entities in multiple dimensions can be difficult and tedious. In this paper, we present a system for synthesizing and recognizing aggregate movements in a virtual environment with a high-level (natural language) interface. The principal components include: an interactive interface for aggregate control based on a collection of parameters extending an existing movement quality model, a feature analysis of aggregate motion verbs, recognizers to detect occurrences of features in a collection of simulated entities, and a clustering algorithm that determines subgroups. Results based on simulations and a sample instruction application are shown.

Populations with purpose

There are currently a number of animation researchers that focus on simulating virtual crowds, but few are attempting to simulate virtual populations. Virtual crowd simulations tend to depict a large number of agents walking from one location to another as realistically as possible. The virtual humans in these crowds lack higher purpose. They have a virtual existence, but not a virtual life and as such do not reasonably depict a human population. In this paper, we present an agent-based simulation framework for creating virtual populations endowed with social roles. These roles help establish reasons for the existence of each of the virtual humans. They can be used to create a virtual population embodied with purpose.

Exploring game design for cybersecurity training

Cybersecurity awareness and cyber skills training are vitally important and challenging. A huge number of attacks against everyday users occur routinely. Prevention techniques and responses are wide ranging but are only effective if used effectively. The objective of this research is to teach everyday users the requisite cybersecurity skills through gaming, beyond the current state of practice. Because the skill level of the trainees is also wide ranging, from causal computer users to software engineers to system administrators to managers, the games must also be capable of training this wide range of computer users. Computer games can provide a media for delivering training in an engaging format at levels appropriate for the individual trainees. In this paper we (1) describe the state of practice by describing the gaming tool used in most cyber challenges at high schools and colleges in the U.S, i.e., the cybersecurity gaming tool CyberNEXS™ (Science Applications International Corporation), (2) outline some of the additional topics that should be addressed in cybersecurity training and (3) note some other approaches to game design that might prove useful for future cybersecurity training game development beyond CyberNEXS.