Sub-system irregularity correction in gaming systems
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Solution Overview
Problem
Existing computer gaming systems lack effective mechanisms for sub-system irregularity correction, which can lead to inconsistencies and unsatisfactory gaming experiences for users.
Innovation Solution
A computing system that monitors user actions, aggregates data, identifies potential irregularities, and automatically generates modified objectives based on user profiles and objectives, communicating these changes to a sub-system for consideration and feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system automatically generates and communicates modified objectives to a sub-system, then sub-system irregularities are corrected and gaming experience consistency is maintained, but system complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by regularly monitoring user actions and pre-aggregating data before irregularities occur. This proactive approach allows the system to identify potential irregularities early and generate modified objectives in advance, maintaining gaming experience consistency without requiring complex real-time intervention mechanisms.
Solution Approach 2:
The system implements a feedback mechanism where modified objectives are communicated to the sub-system, which provides feedback on the changes. This closed-loop feedback allows the system to learn from sub-system responses and refine its irregularity detection and correction processes, reducing the need for increasingly complex correction mechanisms over time.
2Measurement precision
If the system monitors and analyzes aggregated data to identify irregularities, then detection accuracy improves, but data processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing data analysis efforts specifically on detecting irregularities rather than analyzing all data uniformly. By using anomaly detection algorithms that identify deviations from normal patterns, the system achieves high detection accuracy without the need to process and analyze every data point in exhaustive detail, thus reducing overall processing time.
3Productivity
If the system dynamically adjusts objectives based on user profiles and irregularities, then user engagement is enhanced, but system adaptability requirements increase
Solution Approach 1:
The system applies local quality by customizing objective adjustments based on specific user profiles and individual irregularity patterns rather than applying uniform changes to all users. This targeted approach enhances user engagement by making the gaming experience personally relevant while managing adaptability requirements through profile-based segmentation rather than requiring the system to adapt to every possible scenario.
Data Source
AI summary
Systems and methods help the user revise their goals including prompt-based goal revisions and AI-based prediction that based on financial behaviors of the user that shown the system can recommend revised goals. In some instances, a decision tree feedback loop is utilized to automatically modify the goals.