Adaptive recombinant system for dynamic software evolution
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Solution Overview
Problem
Current computer-based information management systems are brittle and limited in their ability to adapt to changing circumstances and user requirements over time, requiring significant human intervention and lacking the capability to dynamically evolve or combine subsets of applications to form new ones.
Innovation Solution
An adaptive recombinant system that tracks and infers user preferences and behaviors to modify its structure and content, enabling it to evolve and adapt autonomously, using a fuzzy network architecture to facilitate structural plasticity and syndication of system subsets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional information management systems (flat files, hypertext models, RDBMS) are used, then system structure is stable and manageable, but the system lacks adaptability to changing circumstances and user requirements
Solution Approach 1:
The patent implements dynamic systems where software components can self-modify and evolve over time based on usage patterns and user interactions. The system transitions from static structures to dynamic, adaptive architectures that automatically adjust to changing requirements without manual intervention.
Solution Approach 2:
The patent enables systems to autonomously adapt and reconfigure themselves through self-modifying code and automated learning mechanisms. The system serves itself by automatically detecting usage patterns, inferring user preferences, and modifying its own structure and behavior without external human intervention.
2Adaptability or versatility
If monolithic computing applications are used, then system structure is simple and unified, but the system cannot be dynamically separated and recombined to form new applications
Solution Approach 1:
The patent decomposes monolithic applications into independent, modular software components that can be separately developed, deployed, and recombined. These modular units can be dynamically assembled to create new applications, enabling extensibility while maintaining manageable complexity through standardized interfaces.
Solution Approach 2:
The patent creates universal software components that can serve multiple functions and be reused across different applications. These modular elements are designed to be context-independent and can be combined in various configurations to fulfill different functional requirements.
3Productivity
If systems require direct human intervention for adaptation, then system behavior is predictable and controllable, but significant manual effort and time are required
Solution Approach 1:
The patent implements continuous feedback loops where the system monitors its own usage patterns, performance metrics, and user interactions. This feedback information is automatically processed to trigger adaptive modifications, enabling the system to evolve rapidly in response to changing conditions without human intervention.
Solution Approach 2:
The patent employs automated inference mechanisms that anticipate user needs and system requirements before they explicitly manifest. The system proactively modifies its behavior and structure based on predicted trends, reducing the need for reactive manual adjustments and accelerating system evolution.
Data Source
AI summary
An adaptive self-modifying system, a recombinant fuzzy network system, and an adaptive recombinant system are disclosed. The adaptive self-modifying system includes functions and algorithms for the self modification of structural elements, including relationships among system objects of the adaptive self-modifying system, based at least in part on usage behaviors associated with the system. The recombinant and adaptive recombinant systems feature functions for syndicating and combining fuzzy networks. The combining of the structural elements of the adaptive recombinant system may be based, at least in part, on usage behaviors associated with the system, and may be preferentially recombined based on evaluations of network “fitness.”