Vortex Composite Entities Through DAG Attribute Synthesis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems lack the ability to effectively synthesize and simulate composite entities in virtual worlds, particularly in the context of virtual tennis players, by integrating aesthetics and performance attributes to create a composite entity that can be shared and consumed, while addressing user preferences and improving player performance.
Innovation Solution
A computer-implemented method that derives a list of aesthetics and performance attributes, generates a directed acyclic graph (DAG), identifies prime aesthetics and performance attributes through independence testing, defines logarithmic spiral expressions, and mixes these attributes to generate a composite entity, which can be shared and consumed, using techniques like feed forward networks (FFNs) and simulated competitions to refine the entity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple aesthetics and performance attributes are integrated to create a composite entity, then the entity accurately reflects user preferences and enhances player performance, but the system complexity increases due to deriving attributes, generating DAG, independence testing, and mixing logarithmic spiral expressions
Solution Approach 1:
The system segments the composite entity creation process into distinct modules: deriving aesthetics and performance attributes, generating a directed acyclic graph (DAG) to model relationships, performing independence testing to identify prime attributes, and mixing logarithmic spiral expressions. This segmentation allows each module to handle specific tasks independently, managing overall system complexity while achieving accurate composite entities.
Solution Approach 2:
The patent introduces a DAG as an intermediary structure to represent relationships between aesthetics and performance attributes. This intermediary enables systematic analysis through independence testing and facilitates the mixing process by providing a structured framework, thereby managing complexity while maintaining measurement precision.
2Manufacturing precision
If independence testing and logarithmic spiral expressions are used to identify and mix prime attributes, then the composite entity quality improves, but the computational time and processing resources increase
Solution Approach 1:
The system performs preliminary independence testing on the DAG to identify prime aesthetics and performance attributes before the actual mixing process. By pre-identifying which attributes are independent and prime, the system avoids redundant computations during the mixing phase, reducing overall computational time while maintaining high composite entity quality.
Solution Approach 2:
The patent transforms attributes into logarithmic spiral expressions, changing the parameter representation from discrete attribute values to continuous mathematical functions. This parameter transformation enables efficient mixing through mathematical operations on the spiral expressions, improving computational efficiency while maintaining attribute quality.
3Measurement precision
If the system derives and tests multiple attributes through DAG and independence testing, then the composite entity accurately represents user preferences, but the ease of operation decreases due to the complex process steps
Solution Approach 1:
The system performs self-service by automatically deriving aesthetics and performance attributes, generating the DAG structure, conducting independence testing, and identifying prime attributes without requiring manual user intervention for each step. Users simply provide their preferences, and the system autonomously completes the complex processing to create accurate composite entities.
Solution Approach 2:
By transforming attributes into logarithmic spiral expressions, the system changes the operational parameters from manual attribute selection and weighting to automated mathematical mixing. This parameter change simplifies user interaction while maintaining precise representation of user preferences through the mathematical framework.
Data Source
AI summary
A computer-implemented method for generating a composite entity is provided. The computer-implemented method includes deriving a list of aesthetics and performance attributes for an entity, generating a directed acyclic graph (DAG) from the aesthetics and the performance attributes, identifying prime aesthetics and prime performance attributes through independence testing of the DAG, defining logarithmic spiral expressions for each of the prime aesthetics and for each of the prime performance attributes, receiving a user input of selections of the prime aesthetics and the prime performance attributes and generating a composite entity from the selections of the prime aesthetics and the prime performance attributes through mixing of the logarithmic spiral expressions of the selections of the prime aesthetics and the prime performance attributes.