5 ways AI is changing game development

by Analytics Insight

February 24, 2022

Game studios are using AI in multiple ways to enrich their releases, and its use will only grow in the future.

Gaming has grown from an engaging pastime to a full-fledged, mainstream activity. According to the latest trend reports, gamers expect captivating experiences and the latest technology in the products they consume. Development engines have evolved to the point where even simple computer-based hobbies such as solve puzzles online have changed in nature.

AI has played a major role in pushing games to where they are right now. Game studios are using AI in multiple ways to enrich their releases, and its use will only grow in the future. Here are 5 ways AI is changing game development.

Find your way

Games these days have engaging storylines and sophisticated worlds as standard. Players expect highly textured environments that entertain and challenge them. For example, players regularly take game characters on long exploration journeys, with the goal of exploring the limits of the game universe.

Guidance, or the act of coding a character’s navigation in the game, is an important game development task. Given the open nature of the average gaming universe these days, developers need to consider several factors when plotting a character’s path.

For example, if a user decides to take their character out exploring in the middle of a quest or main task, how will the character interact with other nearby characters? How will they navigate their terrain and how will the status of the main quest affect the path they take between waypoints in the game?

AI models these complex scenarios and is built into most game engines. This way, game logic changes in real time and can adapt to almost any decision the user makes. The result is an engaging experience that almost feels like the real world.

Object detection

By navigating in a game universe, the characters falling on objects in the game. Users can detect objects quite easily. For example, a vehicle can be used to navigate from one point to another. However, the game character is just a piece of code and may have trouble identifying every variation an object has.

For example, from a coding perspective, a fully functional and undamaged vehicle is different from a damaged vehicle that can still travel short distances. A user can decide to “walk” to the next destination or use the damaged vehicle. To perform the latter task, the game character must identify the damaged vehicle as a candidate for a task and engage with it in the expected manner.

If the character mistakenly mistakes the damaged vehicle for a tree and refuses to drive it, users will not hesitate to point out these faults. AI is used to create intelligent in-game characters that are more likely to correctly identify objects and their variations.

character design

Game characters have become almost human, and users expect the required functionality from them. For example, the characters must react with the right emotional tones and the right facial expressions. There’s another benefit to designing human-like characters. The emotions that these characters can express allow developers to design complex storylines.

For example, a character who can convincingly express a single emotion will not play a convincing role in a storyline with emotional depth. AI, in the form of deep learning algorithms, can now process game mechanics and display appropriate emotions. These algorithms also inform character actions, voices, and dialogue.

The result is an immersive experience gamers will never forget.

Engineering complex game scenarios

Games are becoming more and more open, with in-game character choices guiding the narrative. Coding these possibilities in advance, while anticipating how one choice affects another, is a very complicated task. In most cases, it is impossible to accurately predict which direction the story should go.

AI comes to the rescue and plays a role in creating finite state machine (FSM) models for game development. FSM models allow developers to code multiple scenarios into a single package and let the game engine calculate and choose the ideal path to follow. So developers can give players almost infinite freedom and let the AI ​​do the heavy lifting when processing game logic.

Game Analysis

As the game’s codebases become more complex, code review and bug fixing is a difficult task. There are many nooks and crannies in games these days, and locating the source of an error is nearly impossible, given the vast areas that developers have to search.

AI is used to quickly perform code testing and isolate potential errors and breaks in code. Games these days are platform independent. An error on desktop may not show up on mobile or vice versa. Isolating platform-specific errors is a difficult task, and AI comes to the rescue.

AI-powered game analytics isolate crashes and prevent faulty code releases. This gives developers timely alerts to act on and prevent major flaws in their releases.

Many applications

AI is quickly becoming a central part of game development as technology improves. Undoubtedly, we will see a wider range of applications in the future as games reach higher levels of sophistication.

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Analytics Insight is an influential platform dedicated to ideas, trends and opinions from the world of data-driven technologies. It monitors the developments, recognition and achievements of artificial intelligence, big data and analytics companies across the world.

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