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Discusses some of the key issues that must be addressed in creating virtual humans, or androids. As a first step, we overview the issues and available tools in three key areas of virtual human research: face-to-face conversation, emotions and personality, and human figure animation. Assembling a virtual human is still a daunting task, but the building blocks are getting bigger and better every day. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Building a virtual human is a multidisciplinary effort, joining traditional artificial intelligence problems with a range of issues from computer graphics to social science. Virtual humans must act and react in their simulated environment, drawing on the disciplines of automated reasoning and planning. To hold a conversation, they must exploit the full gamut of natural language processing research, from speech recognition and natural language understanding to natural language generation and speech synthesis. Providing human bodies that can be controlled in real time delves into computer graphics and animation. And because an agent looks like a human, people expect it to behave like one as well and will be disturbed by, or misinterpret, discrepancies from human norms. Thus, virtual human research must draw heavily on psychology and communication theory to appropriately convey nonverbal behavior, emotion, and personality. Comments Author(s)Jonathan GratchThis broad range of requirements poses a serious problem. Researchers working on particular aspects of virtual humans cannot explore their component in the context of a complete virtual human unless they can understand results across this array of disciplines and assemble the vast range of software tools (for example, speech recognizers, planners, and animation systems) required to construct one. Moreover, these tools were rarely designed to interoperate and, worse, were often designed with different purposes in mind. For example, most computer graphics research has focused on high fidelity offline image rendering that does not support the fine-grained interactive control that a virtual human must have over its body.In the spring of 2002, about 30 international researchers from across disciplines convened at the University of Southern California to begin to bridge this gap in knowledge and tools (see www.ict.usc.edu/~vhumans). Our ultimate goal is a modular architecture and interface standards that will allow researchers in this area to reuse each other's work. This goal can only be achieve...

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This paper describes the virtual humans developed as part of the Mission Rehearsal Exercise project, a virtual reality based training system. This project is an ambitious exercise in integration, both in the sense of integrating technology with entertainment industry content, but also in that we have joined a number of component technologies that have not been integrated before. This integration has not only raised new research issues, but it has also suggested some new approaches to difficult problems. We describe the key capabilities of the virtual humans, including task representation and reasoning, natural language dialogue, and emotion reasoning, and show how these capabilities are integrated to provide more human-level intelligence than would otherwise be possible.

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The effectiveness of simulation-based training for individual tasks -such as piloting skills -is well established, but its use for team training raises challenging technical issues. Ideally, human users could gain valuable leadership experience by interacting with synthetic teammates in realistic and potentially stressful scenarios. However, creating human-like teammates that can support flexible, natural interactions with humans and other synthetic agents requires integrating a wide variety of capabilities, including models of teamwork, models of human negotiation, and the ability to participate in face-to-face spoken conversations in virtual worlds. We have developed such virtual humans by integrating and extending prior work in these areas, and we have applied our virtual humans to an example peacekeeping training scenario to guide and evaluate our research. Our models allow agents to reason about authority and responsibility for individual actions in a team task and, as appropriate, to carry out actions, give and accept orders, monitor task execution, and negotiate options. Negotiation is guided by the agents' dynamic assessment of alternative actions given the current scenario conditions, with the aim of guiding the human user towards an ability to make similar assessments.

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