Network-Based Training System Using Virtual Reality Agents
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Solution Overview
Problem
Traditional training methods, such as simulator-based training, are labor-intensive, costly, and inefficient, with high staff-to-trainee ratios and limited accessibility, leading to inadequate monitoring and assessment of trainee skills, especially in cyber operations.
Innovation Solution
A network-based training system that deploys and monitors virtual training simulations and exercises using virtual reality (VR) technology, allowing for remote access and objective monitoring through software agents, enabling efficient skill demonstration and evaluation within a web browser environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional simulator-based training is used, then trainees can receive hands-on training experience, but the training becomes labor-intensive and costly with high staff-to-trainee ratios
Solution Approach 1:
The patent creates virtual copies of training environments and scenarios that can be replicated indefinitely without additional instructional resources. Virtual training scenarios are delivered through web browsers, allowing multiple trainees to simultaneously access identical or varied training content without requiring proportional increases in staff or physical simulators.
Solution Approach 2:
The system implements automated monitoring and assessment through software agents that track trainee actions, collect interaction data, and evaluate skill demonstration without continuous human oversight. This self-service capability allows the system to autonomously manage training delivery and assessment, reducing the staff-to-trainee ratio while maintaining assessment accuracy.
2Ease of operation
If traditional training methods are used, then trainees can receive instruction, but accessibility is limited and resource management is inefficient
Solution Approach 1:
The training system is designed to be platform-agnostic and accessible through standard web browsers, eliminating the need for specialized hardware or software installations. The same infrastructure can deliver diverse training scenarios across different devices and locations, maximizing accessibility while minimizing the complexity of dedicated training facilities.
Solution Approach 2:
The patent introduces a web-based intermediary layer that sits between the training content and trainee devices. This intermediary delivers virtual training scenarios through standard web protocols, allowing trainees to access training without complex local installations while the server infrastructure manages all training delivery and monitoring centrally.
3Measurement precision
If more instructors are deployed to monitor trainees, then skill demonstration can be better assessed, but costs increase and efficiency decreases
Solution Approach 1:
Software agents are deployed to autonomously monitor trainee actions, collect interaction data, and assess skill demonstration without requiring human instructors for continuous observation. The system self-evaluates trainee performance against predefined criteria, eliminating the need for proportional increases in instructional staff while maintaining monitoring accuracy.
Solution Approach 2:
The system implements automated feedback loops where software agents continuously monitor trainee actions, compare them against expected skill demonstrations, and provide real-time or post-session assessment. This automated feedback mechanism maintains high measurement precision without the escalating costs of human monitoring resources.
Data Source
AI summary
Techniques are described for implementing a system that deploys and monitors training simulations and exercises across a network, and that enables the development and execution of virtual training. An example system outputs, for display in a web browser of a trainee computing system, a graphical user interface that includes one or more training exercises, and initiates execution of software agent(s) associated with skill(s) to be demonstrated by a trainee. The example system outputs, at the trainee computing system, content corresponding to scene(s) of an at least partially virtual environment for a training exercise, where the content is rendered for display at least in the web browser of the trainee computing system. After receiving interaction data collected by the software agent(s) during the training exercise, the example system determines, based on the interaction data, that the skill(s) associated with the training exercise have been demonstrated.