SPA：使用命题规划的共享虚拟环境中代理和化身之间的语言交互
SPA: Verbal Interactions between Agents and Avatars in Shared Virtual Environments using Propositional Planning
摘要：
我们提出了一种新的方法，用于在共享虚拟环境中生成虚拟类人代理和用户化身之间的合理的口头交互。Sense-Plan-Ask（SPA）扩展了命题规划和自然语言处理的先前工作，使代理能够利用不确定的信息进行规划，并利用与其他代理和化身的问答对话来获得所需的信息并完成其目标。代理另外能够使用自然语言来响应来自化身和其他代理的问题，从而实现实时多代理多化身通信环境。我们的算法可以模拟数十个虚拟代理在交互速率交互，移动，通信，规划和重新规划。我们发现，我们的算法创建了一个小的运行时成本，使代理更有效地完成他们的目标比代理没有能力利用自然语言通信。我们展示了一组模拟基准的定量结果，并详细介绍了初步的用户研究的结果，以评估由SPA产生的虚拟交互的可扩展性。总的来说，我们发现，参与者更喜欢SPA在84%的响应，包括自然语言交互的可扩展性和这些交互的积极影响方面的显着好处先前的技术。
英文摘要：
We present a novel approach for generating plausible verbal interactions between virtual human-like agents and user avatars in shared virtual environments. Sense-Plan-Ask, or SPA, extends prior work in propositional planning and natural language processing to enable agents to plan with uncertain information, and leverage question and answer dialogue with other agents and avatars to obtain the needed information and complete their goals. The agents are additionally able to respond to questions from the avatars and other agents using natural-language enabling real-time multi-agent multi-avatar communication environments. Our algorithm can simulate tens of virtual agents at interactive rates interacting, moving, communicating, planning, and replanning. We find that our algorithm creates a small runtime cost and enables agents to complete their goals more effectively than agents without the ability to leverage natural-language communication. We demonstrate quantitative results on a set of simulated benchmarks and detail the results of a preliminary user-study conducted to evaluate the plausibility of the virtual interactions generated by SPA. Overall, we find that participants prefer SPA to prior techniques in 84\% of responses including significant benefits in terms of the plausibility of natural-language interactions and the positive impact of those interactions.
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