Personal Virtual Agents for Heterogeneous Device Automation
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Solution Overview
Problem
Existing systems struggle with automating heterogeneous devices and processes due to generic automation solutions causing hardware and software faults, particularly when accessing disparate remote storage devices with differing configurations.
Innovation Solution
The generation of personal virtual agents tailored to individual users based on historical interactions and machine-learning models, which provide customized services by connecting user devices to appropriate domains through personalized communication interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If generic automation solutions are implemented, then automation coverage is improved, but system reliability deteriorates due to hardware and software faults in heterogeneous devices
Solution Approach 1:
The patent segments the automation system into multiple virtual agents, each specialized for specific device types or functions. Instead of one generic automation solution, the system divides automation into specialized components that can handle heterogeneous devices without causing conflicts, thus maintaining both high automation coverage and system reliability.
Solution Approach 2:
The system dynamically changes parameters by generating virtual agents with customized configurations based on device characteristics. Each virtual agent is tailored to specific device parameters (hardware configuration, software version, communication protocols), allowing the automation system to adapt to heterogeneous devices while maintaining reliability through parameter-specific optimization.
2Ease of manufacture
If generic automation solutions are used, then ease of implementation is improved, but adaptability to heterogeneous devices deteriorates
Solution Approach 1:
The system implements self-service through automatic generation of virtual agents based on device profiles. When a new device is added, the system automatically creates a customized virtual agent for that device without manual configuration, maintaining ease of implementation while achieving high adaptability to heterogeneous devices through automated parameter extraction and agent customization.
Solution Approach 2:
The automation system becomes dynamic by continuously adapting virtual agent configurations based on device characteristics and performance feedback. The system can dynamically adjust agent parameters, add new agents for new device types, and modify existing agents based on changing device states, thereby maintaining both ease of implementation and high adaptability.
3Measurement precision
If personal virtual agents are generated for each user, then response accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies universality by creating a standardized virtual agent framework that can serve multiple users and device types. The core virtual agent architecture is universal and reusable, while only the specific parameters and configurations need to be customized for each user. This approach maintains high response accuracy through personalization while controlling device complexity through framework reuse.
Solution Approach 2:
The system uses copying by generating virtual agents through templates and prototypes. Instead of creating entirely new agents for each user, the system copies and customizes base agent configurations, extracting relevant parameters from user profiles and device characteristics. This copying approach achieves high response accuracy through personalized parameters while reducing complexity by reusing proven agent frameworks.
Data Source
AI summary
Systems and method are provided for generating personal virtual agents. A computing device may receive communication request from a first device associated with a particular domain. In response, the computing device may facilitate a connection between the first device and a personal virtual agent that was generated for a user corresponding of, wherein the first device. The computing device may execute the personal virtual agent using a subsequent communication from the first device to generate a response. The computing device may generate an accuracy metric corresponding to the response generated by the personal virtual agent. The personal virtual agent may be trained using the accuracy metric to improve subsequent response generated by the personal virtual agent with respect to the user of the first device.