Arno Hartholt, Edward Fast, Zong-yong Li, Kevin Kim, Andrew Leeds, S. Mozgai
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引用次数: 0
Abstract
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.
智能虚拟代理(IVAs)的研究与开发本身就是一个复杂的过程。我们的目标是通过将学术和商业方法的最佳方面结合到一个原则性的研发平台中来管理这种复杂性，该平台强调互操作性、可扩展性、重用性和对多个硬件目标的支持。这个IVA平台(Virtual Human Toolkit 2.0)是我们早期工作的重新架构，并将模块化消息传递架构与微服务架构相结合。本文讨论了我们的方法、设计决策、经验教训以及正在进行的工作的当前状态。我们将说明架构的优势，如何在自己的工作中最好地使用商品AI云服务，以及如何将遗留的独立软件移植到web服务。
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