The research and development (R&D) of intelligent virtual agents (IVAs) is inherently complex.We aim to manage this complexity by releasing a major update to the Virtual Human Toolkit, combining the best aspects of academic and commercial approaches into a principled R&D platform that emphasizes interoperability, extendability, re-use, and support for multiple hardware targets.We demonstrate the current status of the VHToolkit on Windows desktop and Quest 3 AR/VR headset.

As the demand for socially intelligent Virtual Humans (VHs) increases, so follows the demand for effective and efficient cross-discipline collaboration that is required to bring these VHs “to life”. One avenue for increasing cross-discipline fluency is the aggregation and organization of seemingly disparate areas of research and development (e.g., graphics and emotion models) that are essential to the field of VH research. Our initial investigation (1) identifies and catalogues research streams concentrated in three multidisciplinary VH topic clusters within the domain of social intelligence, Emotion, Social Behavior, and The Face, (2) brings to the forefront key themes and prolific authors within each topic cluster, and (3) provides evidence that a full scoping review is warranted to further map the field, aggregate research findings, and identify gaps in the research. To enable collaboration, we provide full access to the refined VH cluster datasets, key word and author word clouds, as well as interactive evidence maps.

The research and development (R&D) of intelligent virtual agents (IVAs) is inherently complex. We aim to manage this complexity by combining the best aspects of academic and commercial approaches into a principled R&D platform that emphasizes interoperability, ex-tendability, re-use, and support for multiple hardware targets. This IVA platform, the Virtual Human Toolkit 2.0, is a re-architecture of our earlier work and combines a modular message passing architecture with that of a microservices architecture. This paper discusses our approach, design decisions, lessons learned, and current status of this ongoing effort. We illustrate the strengths of the architecture, how best to use commodity AI cloud services in one's own work, and how to port legacy stand-alone software to a web service.

A major impediment to the success of virtual agents is the inability of non-technical experts to easily author content. To address this barrier we present VHMason, a multimodal authoring tool designed to help creative authors build embodied conversational agents. We introduce the novel aspects of this authoring tool and explore a use case of the creation of an agent-led educational experience implemented at Children's Hospital Los Angeles (CHLA).