Dynamic Constraint Solver with Part-Whole Hierarchy
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Solution Overview
Problem
Existing constraint satisfaction problem (CSP) solvers are inefficient in handling large sets of variables with conditional structures, failing to provide significant space savings and segment related variables into sub-problems effectively.
Innovation Solution
A dynamic constraint solver that employs a part-whole hierarchy model, assigning variables such as Selected, Quantity, and Relative Quantity to each part, and automatically applies constraints to optimize performance and minimize solution size by classifying parts as static or dynamic based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional CSP solvers are used to handle large sets of variables with conditional structures, then the solver can process the problem, but the solver fails to provide significant space savings and cannot effectively segment related variables into sub-problems
Solution Approach 1:
The patent segments the CSP into sub-problems by introducing a part-whole hierarchy that divides variables into parts (individual variables) and wholes (groups of related variables). This allows the solver to process large CSPs by breaking them down into manageable sub-problems that can be solved independently and then composed, achieving both space savings and effective segmentation of related variables.
Solution Approach 2:
The patent implements a nested part-whole hierarchy where sub-problems are nested within larger problems. Each part can be independently solved and then composed with other parts to form the complete solution. This nesting structure enables the solver to handle large CSPs by recursively solving smaller sub-problems, achieving significant space savings while maintaining the ability to segment and process complex variable relationships.
2Adaptability or versatility
If Conditional CSP or Generative CSP approaches are used, then variables can be activated or deactivated, but these approaches do not provide real space savings and do not allow for segmentation of related variables into sub-problems
Solution Approach 1:
The patent segments variables into parts and wholes within a hierarchical structure, allowing related variables to be grouped together in sub-problems. This segmentation enables the solver to process only the relevant parts of the CSP at any given time, achieving real space savings while maintaining adaptability through the part-whole hierarchy that can dynamically organize variables based on problem requirements.
Solution Approach 2:
The patent introduces dynamic capabilities to the part-whole hierarchy, allowing the structure to adapt and reorganize based on problem requirements. The hierarchy can dynamically add, remove, or reconfigure parts and wholes as needed, providing both space savings through selective processing and versatility through adaptive reconfiguration of the CSP structure.
Data Source
AI summary
A constraint solver for solving a constraint satisfaction problem model which includes at least one part-whole hierarchy assigns variables to each part of the part-whole hierarchy. The variables include at least one of selected, quantity, and relative quantity, wherein each part has a parent. The solver automatically applies at least one part-whole hierarchy constraint to the part and solves the model and generates a solution.