Meta-Solver Framework for Multi-Domain Problem Solving
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current computing systems lack an efficient framework for solving complex problems across various disciplines, such as mathematics, science, and engineering, as they often require multiple solvers and starting points, which can be cumbersome and inefficient.
Innovation Solution
A technical computing environment (TCE) with a meta-solver and sub-solvers framework that identifies and utilizes multiple solvers and points to find solutions, employing a point framework to generate and cache points for use by solvers, optimizing the problem-solving process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple solvers and starting points are used to solve complex problems, then solution accuracy and reliability improve, but system complexity and operational difficulty increase
Solution Approach 1:
The patent introduces a meta-solver as an intermediary component that manages multiple sub-solvers and starting points. The meta-solver coordinates the selection and execution of appropriate sub-solvers based on problem characteristics, thereby maintaining high solution reliability while shielding users from the complexity of managing multiple solvers directly.
Solution Approach 2:
The solver framework is segmented into hierarchical levels: a meta-solver at the top level and multiple specialized sub-solvers at lower levels. This segmentation allows each component to have specific, simplified responsibilities, improving overall system reliability through specialized functionality while reducing operational complexity through clear division of labor.
2Reliability
If multiple solvers and starting points are used to solve complex problems, then solution accuracy and reliability improve, but ease of operation deteriorates
Solution Approach 1:
The meta-solver implements self-service by automatically selecting appropriate sub-solvers and starting points based on problem characteristics without requiring user intervention. This maintains high solution reliability through multiple solvers while significantly improving ease of operation, as users simply need to provide the problem statement rather than configure multiple solvers manually.
Solution Approach 2:
The meta-solver acts as an intermediary between the user and the complex solver infrastructure. It translates user problems into appropriate solver configurations automatically, maintaining reliability through multiple solvers while hiding operational complexity from users.
3Productivity
If a comprehensive framework with multiple solvers is implemented, then problem-solving effectiveness improves, but computational time and resources increase
Solution Approach 1:
The framework performs preliminary actions by pre-classifying problems and pre-selecting appropriate sub-solvers before actual computation begins. The meta-solver analyzes problem characteristics upfront and chooses the most efficient solver combination, thereby improving overall productivity while minimizing unnecessary computational time spent on inappropriate solver configurations.
Solution Approach 2:
The solver framework is dynamic in that the meta-solver can adaptively select and switch between different sub-solvers based on problem characteristics and performance feedback. This dynamic adaptation improves productivity by using the most efficient solver for each specific problem while avoiding wasted computational time on unsuitable solvers.
Data Source
AI summary
In an embodiment, information for use in identifying a plurality of sub-solvers may be acquired. The plurality of sub-solvers may be used in a first attempt to find at least one solution to a problem that may be defined in the acquired information. At least two of the sub-solvers in the plurality of sub-solvers may be of different sub-solver types. The sub-solvers may be identified based on the acquired information. One or more starting points for the identified sub-solvers may be identified and transferred to the identified sub-solvers. One or more outputs, that indicate one or more results associated with the first attempt to find at least one solution to the problem, may be acquired from the identified sub-solvers. One or more sub-solvers may be identified, based on the acquired one or more outputs, for use in a second attempt to find at least one solution to the problem.