Work

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Year: 2024
Type: article
Abstract: This article establishes the business and technical imperative for AI-driven personalization in the casual and hyper-casual mobile gaming markets. It argues that the traditional era of static game design has reached a point of structural obsolescence. The paper analyzes an industry paradox: while mobile gaming dominates global revenue, the sector is plagued by a retention crisis with Day-1 churn rates frequently exceeding 70%. The root cause is identified as a monolithic design failure, defined as the inability of hard-coded progression curves to adapt to the radical diversity in player skill, motivation, and session availability. Leveraging research and industry data through 2024, the analysis demonstrates how algorithmic adaptation serves as a critical performance lever. The paper details the deployment of two core Machine Learning architectures: (1) Dynamic Difficulty Adjustment (DDA) to programmatically maintain the flow state, and (2) Predictive Player Modeling to preemptively mitigate churn through personalized interventions. The findings indicate that while these systems significantly optimize commercial metrics such as Lifetime Value (LTV), long-term viability depends on a Safety-by-Design approach. The article concludes by presenting a framework for ethical implementation. This framework prioritizes Explainable AI (XAI) and rigorous Data Minimization, particularly regarding child players, to ensure that the transition from a monolithic product to an individualized service is both profitable and responsible.
Author: tho
Language: English
Open Access status: green
OpenAlex ID: W7105758121
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