Dynamic Probability Control for Stochastic Item Provision Systems
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Solution Overview
Problem
The existing probability-based game item provision systems, such as Gacha and upgrade systems, face challenges in maintaining user interest and sales due to difficulties in finding an appropriate probability for item provision, leading to a decline in user engagement.
Innovation Solution
A method is introduced to control the probability of these systems by measuring the amount of use during specific time intervals, comparing it with thresholds, and adjusting the probability within predetermined ranges, thereby providing real-time information to users and service providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed probability is used for item provision, then system simplicity is maintained, but user engagement decreases over time
Solution Approach 1:
The patent implements dynamic probability adjustment where the item provision probability changes based on measured usage amounts. The server dynamically modifies probabilities within predetermined ranges based on whether usage exceeds thresholds, transforming the static probability system into an adaptive one that maintains user engagement while preserving operational simplicity.
2Productivity
If probability is adjusted frequently, then user engagement is maintained, but system control complexity increases
Solution Approach 1:
The patent employs periodic probability adjustment by measuring usage amounts over specific time intervals (first time interval for measurement, second time interval for adjustment). This periodic measurement and adjustment cycle maintains user engagement through dynamic probabilities while preventing excessive control complexity by structuring adjustments in regular intervals rather than continuously.
3Ease of operation
If probability is increased to boost item acquisition, then user satisfaction improves, but system revenue decreases
Solution Approach 1:
The patent implements feedback-based probability control where the server measures actual usage amounts, compares them against thresholds, and adjusts probabilities accordingly. When usage is high, probabilities are increased to maintain satisfaction; when usage is low, probabilities are decreased to protect revenue. This closed-loop feedback mechanism balances user satisfaction and system revenue dynamically.
Data Source
AI summary
The present disclosure provides a method of controlling a probability of a probability-based item provision system, which includes measuring an amount of use of an item provision system during a first time interval, comparing the measurement result with a first threshold, and changing the probability of the item provision system within a predetermined range during a second time interval after the first time interval, based on a result of the comparing.