Analysis of Procedural Content Generation and Stylisation Techniques in Developing Video Games

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Generative AI models significantly enhance context awareness and content richness in video games, improving player experiences.
Experimental findings show that while procedural content generation offers structural diversity, it often lacks depth and context.
The analysis reviews established methods like Perlin noise and generative adversarial networks in enhancing game environments.
Integration of AI-driven approaches in procedural content generation indicates a promising future for dynamic game design frameworks.

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Analysis reveals how generative AI enhances procedural content generation, improving game design and experiences.

Jiemin Xie (2025) studied this question.

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