Mobile game advertisement strategy dynamic optimization method based on double fatigue degree model

By constructing a virtual player group simulation environment with a dual fatigue model, and combining AI agents and systematic search algorithms, the problem of inaccurate churn prediction due to advertising interference in mobile games was solved. This enabled automated optimization of level and advertising strategies, improving game operation efficiency and commercial revenue.

CN121810349BActive Publication Date: 2026-07-03CHENGDU CHENGFENG QUYOU TECHNOLOGY CO LTD
View PDF 2 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-12-31
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

Existing technologies in mobile games fail to effectively consider the impact of advertising interference on player churn, resulting in inaccurate churn predictions, an inability to dynamically optimize the balance between advertising strategies and level difficulty, and a lack of automated optimization methods.

Method used

We construct a virtual player group simulation environment based on a dual fatigue model, use AI agents to evaluate level difficulty and quantify ad fatigue, and combine a dynamic eCPM model and a systematic search algorithm to automatically optimize level and ad strategies to maximize the predicted total lifetime value.

Benefits of technology

It improves the accuracy of player churn prediction, enables automated collaborative optimization of level difficulty and advertising strategies, balances player experience and commercial revenue, reduces reliance on manual testing, and improves game operation efficiency.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN121810349B_ABST
    Figure CN121810349B_ABST
Patent Text Reader

Abstract

This invention provides a dynamic optimization method for mobile game advertising strategies based on a dual fatigue model, comprising: S1. Configuration information acquisition; S2. Level difficulty quantification; S3. Dual fatigue player modeling; S4. Group evolution simulation and index calculation; S5. Optimization strategy triggering and generation; S6. Candidate strategy evaluation and optimal output. This invention aims to address the problem in existing player behavior prediction models that fail to adequately consider advertising interference, leading to inaccurate predictions of player churn in IAA games. Simultaneously, it fills the technological gap by addressing the limitation of existing technologies that can only passively predict and cannot actively and dynamically find the optimal advertising and difficulty balance strategy for IAA games.
Need to check novelty before this filing date? Find Prior Art

Citation Information

Patent Citations

  • Game level generation recommendation method, system, equipment and medium

    CN120617962A

  • Dynamic game difficulty self-adaptive adjustment method and system based on user behavior feedback

    CN120789656A