Data Mining Management Server Mediator Architecture
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Solution Overview
Problem
Existing data mining systems face challenges in deriving useful knowledge from large datasets, particularly in environments like healthcare, smart grids, and financial trading, where extracting patterns is daunting due to the complexity and volume of data.
Innovation Solution
A computer-implemented data mining management system that outputs action signals to a controlled system, utilizing a population of individuals developed by a machine learning system, where a management server selects operations to allow or block these signals based on a management rule set, ensuring coordinated action across independent actors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a large population of independent actors with individual rules is deployed to process data, then the system's ability to derive useful knowledge from large datasets is improved, but the coordination and management complexity of these actors worsens
Solution Approach 1:
A management server is introduced as an intermediary component between the population of independent actors and the controlled system. The management server receives intermediate action signals from multiple actors, evaluates them against management rules, and selects which signals to forward to the controlled system. This mediator architecture enables the system to maintain a large population of diverse actors for improved data processing while centralizing coordination functions to manage complexity.
2Adaptability or versatility
If multiple independent actors assert actions based on their own rules, then the system's adaptability and versatility are improved, but the reliability of achieving system-wide objectives worsens due to potential conflicts
Solution Approach 1:
The management server implements a feedback mechanism where intermediate action signals from actors are evaluated against management rules before being forwarded to the controlled system. The server monitors the assertions made by actors and selectively allows or blocks signals based on whether they align with system-wide objectives. This feedback loop maintains actor diversity and adaptability while ensuring reliability by preventing conflicting actions from being executed.
3Ease of operation
If individual actors operate autonomously with their own rules, then the ease of operation is improved, but the loss of information about system-wide coordination worsens
Solution Approach 1:
The management server serves as an information intermediary that collects intermediate action signals from autonomous actors, evaluates them against management rules containing system-wide coordination information, and forwards selected signals to the controlled system. This architecture preserves actor autonomy and ease of operation while preventing information loss about system-wide coordination through the centralized rule evaluation process.
Data Source
AI summary
A system for outputting an action signal to a controlled system is provided. The system includes a memory storing individuals to be deployed to a production environment as an actor, wherein each of the individuals has a rule associated therewith for asserting an action, and the actor includes one or more individuals, is associated with the controlled system and is configured to transmit an intermediate action signal for asserting the action. The system includes a management server configured to receive the intermediate action signal, select, from a set of available operations, a selected operation to perform with respect to the intermediate action signal, and the set of available operations including allowance and a blocking of the intermediate action signal. Further, in response to the selected operation being the allowance, transmitting the intermediate action signal, and in response to the selected operation being the blocking, blocking the intermediate action signal.