Role of AI in Video Game Development
Artificial Intelligence’s (AI) role in the development of video games has been profound, revolutionizing the way games are designed, played, and experienced. By using Machine Learning (ML) models, video games can take on entirely new levels of realism and immersion.
As AI becomes more sophisticated, its role in video game development is only expected to grow, creating new techniques for developers and gamers to enjoy together. The advent of generative AI from Deep Learning (DL) models is creating new applications that can be integrated into our gaming experiences.
Role of AI in Video Game Development
AI has been an integral part of video game design as far back as 1972 with the release of Pong which featured paddles that reacted to player movement and sped up over time to thwart its human opponent. While rudimentary at the time, the integration of AI into Pong became a massive hit, becoming the first wide-scale success in the new video game industry.
As technology became more sophisticated in the 1980s, so did the integration between AI and video game development which saw new heights following the release of Pac-Man which featured four ghostly non-playable characters (NPCs) controlled by separate AI algorithms. Each ghost followed a separate route using different behavior patterns to trick the player into controlling Pac-Man which was an exponential innovation on its predecessor, Pong, 10 years earlier.
Routines and behavior patterns would only become more sophisticated at the turn of the century following the tech boom and bubble spurred by the launch of the internet. Again, AI took a front-seat role in video game design, applying itself to more complex games like The Sims which mimicked a dollhouse and operated entire households of characters at the same time using unique personalities designed by the player.
Examples of AI in Video Game Design
The digital design of video games provides a great opportunity for deep learning models to be trained. Backed by thriving customer demand, AI can be found in most video game designs:
Non-Playable Character: NPCs play a huge role in video games like Skyrim, helping to provide players with quests and lore or assisting with a task. Developers use Reinforcement Learning algorithms to train these characters so that they act properly in-game.
Procedurally Generated Content: Generative content has become an effective way for developers to retain players with a cycle of new content created in-game. Developed using Generative Adversarial Networks (GANs), this algorithm can create unexplored dungeons or exciting loot for players.
Adaptive Difficulty: Strategy and puzzle games benefit from AI as well, using neural networks and Long Short-Term Memory to predict player behavior over time with sequential data to create more challenging gameplay.
AI in Game Play and User Experience
AI can create significant impacts on world design within a video game as well, helping to improve gameplay and add depth to the user experience. GANs and Convolutional Neural Networks can help establish dynamic in-game weather. Many games ranging from sports and racing to city simulators rely on robust weather systems to challenge the player.
Developers are also starting to explore Natural Language Processing (NLP) in video games as well, giving players an additional layer of gameplay using their voice and language to communicate with NPCs. While still a fringe development in gaming, smaller releases like Her Story and Phasmophobia have seen moderate success with NLP gameplay.
The Future of AI in Video Game Development
While Video Games have become one of AI’s most common playgrounds, there is still a lot of development necessary to reach the full potential of its use. The cost of researching, developing, using, and maintaining more advanced Deep Learning models can be staggeringly high which results in only a few major studios having access to the most advanced AI algorithms.
However, many of the industry’s largest studios rely more on products that appeal to mass audiences. These series, like Madden or Call of Duty, attract sales because their gameplay design is familiar. Introducing wild new AI concepts presents a risk to these established products, leaving it to smaller studios to explore new concepts and design at a slower, but steady, pace.
