Utilizing GenAI for procedural content generation in video games

Despite procedural content generation (PCG) easing development, great games take years. Could Generative AI be the key to faster masterpieces? Gen AI, unlike traditional methods, swiftly generates diverse game elements, enhancing PCG while balancing creative ownership and originality concerns

- Shouvik Mazumdar

As the credits rolled on my TV screen, a feeling of emptiness set in. A five year wait for this beautiful game was done in an eight-hour binge & I simply yearned for the next season to arrive superfast. Game developers have long relied on procedural content generation (PCG) to accelerate game development and minimize manual effort, yet it takes years to develop a great game. Being in this industry, I understand that each masterpiece is a symphony of passion, love, and dedication, where game developers pour their souls into crafting every pixel and line of code to tell a story never told before. But I couldn’t help thinking if Generative AI (Gen AI) is the silver bullet to churn out masterpieces quicker &faster?

PCG involves algorithmically creating various game elements like levels, maps, items, characters, and mechanics instead of handcrafting them. The evolution of PCG can be delineated into three key phases:

Pre AI Era: Before the widespread adoption of AI, PCG operated within strict parameters and rules. Minecraft leveraged PCGx to unlock endless gameplay potential by crafting diverse, boundless worlds, complete with landscapes, caves, and ecosystems. It intelligently employs gradient noise algorithms like Perlin Noise to maintain coherence amid randomness.

AI Infusion: AI integration enhanced PCG with player data analysis, adaptive behaviour, and dynamic content generation. In “The Last of Us Part II” AI-driven NPCs show human-like adaptability, using pathfinding algorithms and decision trees to immerse players and keep the gameplay unpredictable, deeply engaging them in the virtual world.