Parallel Agent System for Modular Expert Rule Management
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Solution Overview
Problem
Large expert systems in fields like medicine are difficult to maintain and update due to the inverse relationship between algorithm complexity and testability, making it challenging to ensure all rules are accurate and current, which hampers their utility in providing timely and informed decision support to professionals.
Innovation Solution
An agent system comprising multiple agents and an agent manager that operate in parallel, allowing for concurrent monitoring and updating of agents, with each agent supported by reference literature for validation, and meta-tagged for organization and searchability, enabling the system to provide timely and appropriate outputs based on current scientific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large expert system with sophisticated algorithms is used to provide comprehensive diagnostic support, then the completeness and thoroughness of the system is improved, but the difficulty of validating and updating rules increases
Solution Approach 1:
The expert system is divided into multiple independent agents, each responsible for specific diagnostic rules or knowledge domains. This segmentation allows individual agents to be validated and updated separately, reducing the overall complexity of maintaining the complete system while preserving comprehensive diagnostic coverage through the collective capability of all agents.
2Reliability
If the expert system includes a large number of rules to ensure thoroughness, then the diagnostic completeness is improved, but the ease of updating new rules deteriorates
Solution Approach 1:
Rules are organized into separate agents that can be independently created, modified, and validated. This modular structure enables straightforward updating of specific rules without affecting the entire system, maintaining thorough diagnostic coverage while significantly improving the ease of rule updates.
Solution Approach 2:
The system allows dynamic addition and removal of agents based on diagnostic needs. New rules can be introduced as new agents without restructuring the existing system, enabling flexible updates while maintaining comprehensive rule coverage.
3Adaptability or versatility
If the expert system is designed to be current with latest information, then the usefulness of the system is improved, but the difficulty of validation and updating increases
Solution Approach 1:
Each agent can be independently validated against its specific knowledge domain, making validation more manageable. The modular structure allows systematic validation of individual agents while maintaining overall system currency through selective updates.
Solution Approach 2:
Agents can be pre-validated and tested independently before being integrated into the system. This preliminary validation approach reduces the complexity of validating the complete system while ensuring that only verified, current information is deployed.
Data Source
AI summary
A system having an agent manager and a plurality of parallel agents for assisting a user in reaching a conclusion is provided in at least one embodiment. In at least one embodiment, the system is in communication with at least one database housing information to be analyzed by at least one of the agents. Further embodiments include the operation of the system and its interaction with the at least one database. In at least one further embodiment, the method includes the development and publication of the agents.