Machine-Learned Virtual Environment Personalization From User Interactions
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Solution Overview
Problem
Existing systems fail to dynamically and efficiently generate customized virtual environments that cater to individual user needs and respond to changing events during interactions in metaverse systems.
Innovation Solution
A system that utilizes a machine learning model to map user behavior and device objects to virtual environment objects, integrating them into interaction objects, and dynamically generates customized virtual environments in real-time, allowing seamless integration with user preferences and behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single metaverse environment is provided to all users, then system complexity is reduced and ease of operation is improved, but adaptability to individual user needs and responsiveness to changing user actions deteriorates
Solution Approach 1:
The system segments the virtual environment into multiple customizable aspects (visual preferences, interaction styles, content types) that can be independently adjusted for each user. This allows the system to provide personalized environments without requiring complete separate systems for each user, thus maintaining manageable complexity while achieving high adaptability.
Solution Approach 2:
The virtual environment is designed to be dynamic rather than static, allowing it to automatically adjust and reconfigure based on real-time user actions, device operations, and detected preferences. This dynamic adaptation enables the system to respond to changing user needs without manual intervention, resolving the contradiction between personalization and system complexity.
2Adaptability or versatility
If customized virtual environments are generated for each user based on real-time behaviors and device operations, then adaptability to user needs is improved, but processing time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-defining environment templates, object types, and configuration options before user interactions begin. This preparation allows the system to quickly assemble customized environments by selecting and combining pre-prepared elements rather than creating everything from scratch, thus reducing processing time while maintaining high adaptability.
Solution Approach 2:
The system uses copying mechanisms to replicate and adapt standardized virtual environment objects and configurations for different users. Instead of creating entirely unique environments for each user, the system copies base templates and modifies them based on user preferences, significantly reducing processing time while still achieving customization and responsiveness.
3Productivity
If the same virtual environment is provided to all users, then processing resources are conserved and productivity is maintained, but the ability to fulfill user individual needs and respond to user actions deteriorates
Solution Approach 1:
The system implements multi-functionality by creating a universal base environment that can serve all users while incorporating adjustable parameters and modular components. This universal framework maintains processing efficiency by reusing common elements across users, while the ability to selectively activate and customize specific components enables the system to respond to individual user needs and actions without sacrificing overall productivity.
Data Source
AI summary
A system for auto-generating and sharing customized virtual environments comprises a processor associated with a server. The processor detects an avatar associated with a user device interacting with virtual environment objects in a virtual environment for an interaction with an entity. The processor generates user data objects associated with the interaction and a user profile. The processor extracts user behavior objects and user device objects from the user data objects. The processor applies a machine learning model to map the user behavior objects and the user device objects to the virtual environment objects. The processor integrates the user behavior objects and the user device objects with the virtual environment objects into a set of interaction objects based on the mapping. The processor determines customized environment virtual objects based on the interaction objects. The processor renders the customized virtual environment objects in a customized virtual environment corresponding to the interaction.


