Validation of virtual humanoid intelligent agents in virtual reality systems

Amela Sadagic
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Abstract

One of the great benefits VR systems offer is their ability to simulate a number of virtual humans when their presence is needed in the context of some learning or training experience. Being that the real humans may not be available to play different roles and support virtual sessions, the ability of a system to generate highly believable representations of autonomous virtual humans - virtual intelligent agents - is vital in achieving specific learning and training objectives. Eliminating the elements of the system that can cause a negative learning and training transfer is a paramount in those systems. We illustrate the results of two user studies focused on validation of non-deterministic domain-specific behaviors generated by our system (example: behaviors typical for a well coordinated group of paramedics or military unit). The results and observations confirmed that when it comes to VR systems with stringent requirements and high expectations for positive learning/training transfer, we still need humans to evaluate and validate synthesized human-like agent behaviors.
虚拟现实系统中虚拟类人智能体的验证
虚拟现实系统提供的一大好处是,当需要虚拟人在学习或培训经验的背景下出现时,它们能够模拟许多虚拟人。由于真实的人类可能无法扮演不同的角色并支持虚拟会话,因此系统生成高度可信的自主虚拟人类表示(虚拟智能代理)的能力对于实现特定的学习和训练目标至关重要。在这些系统中,消除系统中可能导致负面学习和训练转移的元素是至关重要的。我们举例说明了两个用户研究的结果,这些研究关注的是由我们的系统生成的非确定性领域特定行为的验证(例如:由医护人员或军事单位组成的良好协调组的典型行为)。结果和观察证实,当涉及到具有严格要求和对积极学习/训练迁移的高期望的VR系统时,我们仍然需要人类来评估和验证合成的类人代理行为。
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