How is machine learning used in game development today?

Let us take a few moments to analyze the evolution of video gaming. Years ago, classic games like Pac-Man or Super Mario were thriving among gaming enthusiasts. Yet, their popularity has started to pale when the gaming industry has evolved and, in comparison with the new leading games, they no longer display an exciting game world. It is certainly not only about the fact that newer games have better graphics and smoother interfaces. They are far more advanced offering complex scenarios, unique experiences from session to session, unique content, captivating challenges, and unlimited virtual possibilities. They simply do a better job of mimicking real-life aspects and experiences. The reason that stands behind the development of the video gaming industry is undoubtedly machine learning. Nowadays, thanks to machine learning, games have evolved so much that they are becoming more and more addictive. They offer such a complex world with a multitude of possibilities that make gaming enthusiasts love to spend several hours in front of their computers without possibly getting bored with anything that happens in the virtual world.

Nowadays, technological advancements have a major interest in game playing. Artificial intelligence in general and machine learning, in particular, are being used to completely revolutionize the development of the gaming experience. The increasing number of smartphone and tablet users, the introduction of new gaming genres, and the affinity of young generations towards technology create a strong base for the gaming industry to continue to develop and become a fruitful one.

What is machine learning?

First and foremost, to analyze how it has influenced the gaming world, we have to understand what machine learning is. It represents the practice of using algorithms to use data, learn from it, and eventually become more accurate in predicting outcomes without being explicitly programmed. It is pretty obvious from its name why this technology is so exciting. Machine learning gives the computer something that it used to be specific to humans, and that is the ability to learn. The main skills that are incorporated in machine learning include expertise in computer fundaments, data modeling and evaluation skills, knowledge of probability and statistics and in-depth knowledge of programming skills. The main purpose of its use is to personalize every experience specifically for its user. Using statistical analysis and predictive analytics, machine learning identifies patterns in the user’s data and personalizes the user’s experience.  This technology is being used in a wide range of applications today. Companies from all industries use data science vs machine learning, and analytics to help them drive swift business decisions efficiently.  The same goes for the use of it in game development.

How is machine learning used in video games?

Since its appearance, machine learning has completely revolutionized almost every industry. Industries such as healthcare, agriculture, and education are more widely discussed as they have a bigger impact on humanity. Yet, the use of machine learning and how it has changed the gaming industry is acknowledged and discussed only by gaming enthusiasts.  

When applied to video games, machine learning is changing its development using the same principle. It feeds the system or algorithm with different information and observations which are later used to make predictions about future outcomes. One of the most commonly used methods by game developers is reinforcement learning. It is a learning method that uses rewards or punishments to teach the system what is right and what is wrong. Eventually, after analyzing and learning those choices, the system starts to recognize the certain set of actions that it has to perform to achieve positive results.

The machine learning algorithms can respond to a player’s actions dynamically and in more imaginative ways. Machine learning has certainly helped game development in areas including level and map generation, texture generation, artificial players, audio generation and much more. Using human players’ actions as the training data, the algorithm trains four times faster than reinforcement training alone. Therefore, the NPSs opponents in a video game will respond to your actions in unique and unexpected ways.

Another challenge which game developers overcome by using machine learning is to model the real world in the game. Today’s games are expected to be more immersive and realistic. So, a machine learning algorithm is used to predict the downstream effects of a player’s actions. Modeling complex systems are one of the many abilities of a machine learning algorithm.

The increasing number of smartphone and tablet users has brought up another challenge for the gaming industry. Playing on the mobile phone seems to be the new trend among the video games’ enthusiasts as it is more convenient because they are easy to pick up and play. According to the statistics, the mobile gaming sector is right now the highest revenue earner in the whole gaming industry. However, mobile games have been limited in scope as the phoned do not have the processing power and the graphics of a console or a computer. Therefore, the gaming industry had to find a way to offer the players more engaging mobile games. Machine learning is used to slowly change those limitations with AI chips to add specialized processing power. Mobile games will continue to improve and become more realistic, interactive, and immersive similar to the video games designed for computers.

Audio sound effects or music are vital for creating a unique experience for the players. A custom designed soundtrack for game development can be created with machine learning for better engaging the player in the virtual world of the game.

Machine learning promises to make a meaningful impact on user experience, retention, and revenue for gaming. It is clear that video games are getting better with time thanks to technological advancements. The gaming industry is still very much in the early stages of using machine learning to power the gaming experiences of the players. Yet, there are limitless possibilities that still have time to be explored and to grow.

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