Creating a Newer and Improved Procedural Content Generation (PCG) Algorithm with Minimal Human Intervention for Computer Gaming Development

Procedural content generation (PCG) algorithms have become increasingly vital in video games developed by small studios due to their ability to save time while creating diverse and engaging environments, significantly enhancing replayability by ensuring that each gameplay experience is distinct. Previous research has demonstrated the effectiveness of PCG in generating various game elements, such as levels and weaponry, with unique attributes across different playthroughs. However, these studies often face limitations in processing efficiency and adaptability to real-time applications. The current study introduces an improved spawn algorithm designed for 2D map generation, capable of creating maps with multiple room sizes and a decorative object. Unlike traditional methods that rely solely on agent-based evaluations, this constructive algorithm emphasizes reduced processing power, making it suitable for generating small worlds in real time, particularly during loading screens. Our findings highlight the algorithm’s potential to streamline game development processes, especially in resource-constrained environments, while maintaining high-quality content generation.