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Gaming has gone from an engaging pastime to a full-fledged, mainstream activity. According to the latest trend reports, gamers expect engaging experiences and the latest technology in the products they consume. Development engines have advanced to the point where even simple, computerized pastimes such as solving online jigsaw puzzles have changed in nature.
AI has played a major role in pushing games to where they are currently. Game studios use AI in multiple ways to enrich their releases, and its use is only set to grow in the future. Here are 5 ways AI is changing game development.
Games these days have engaging storylines and sophisticated worlds as standard. Players expect highly textured environments that both entertain and challenge them. For instance, players routinely take in-game characters on long exploratory journeys, in a bid to explore the limits of the game's universe.
Pathfinding, or the act of coding an in-game character's navigation, is an important game development task. Given the open nature of the average game's universe these days, developers must take several factors into account when plotting a character's path.
For instance, if a user decides to take their character exploring in the middle of a main quest or task, how will the character interact with other characters nearby? How will they navigate their terrain, and how will the status of the primary quest affect the path they will take between in-game waypoints?
AI models these complex scenarios and is embedded into most gaming engines. This way, the game's logic changes in real-time and can accommodate almost any decisions the user makes. The result is an engaging experience that feels almost like the real world.
While navigating an in-game universe, characters will stumble upon in-game objects. Users can detect objects pretty easily. For instance, a vehicle can be used to navigate from one point to another. However, the in-game character is just a piece of code and might struggle to identify every variation an object presents.
For instance, from a coding perspective, a fully functioning, pristine vehicle is different from a damaged one that can still travel short distances. A user might decide to "walk" to the next destination or use the damaged vehicle. To execute the latter task, the in-game character must identify the damaged vehicle as a candidate for a task and engage with it in an expected fashion.
If the character misidentifies the damaged vehicle as a tree and refuses to drive it, users will not hesitate to point out these flaws. AI is being used to create intelligent in-game characters that are more likely to correctly identify objects and their variations.
Game characters have become almost human-like, and users expect the requisite features from them. For instance, characters must react with the right emotional tones and facial expressions. There is another advantage to designing near-human-like characters. The emotions these characters can express allow developers to design complex storylines.
For instance, a character that can convincingly express just one emotion isn't going to play a convincing role in a storyline with emotional depth. AI, in the form of deep learning algorithms, can now process in-game mechanics and display appropriate emotions. These algorithms also inform character actions, voices, and dialogue.
The result is an immersive experience that gamers will never forget.
Games are becoming more open-ended, with in-game character choices driving the narrative. Coding these possibilities beforehand, while anticipating how one choice affects another, is a highly complicated task. In most cases, it's impossible to accurately predict which way the story ought to head.
AI is coming to the rescue and is playing a part 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 compute and choose the ideal path to take. Thus, developers can give gamers almost infinite freedom and let AI do the heavy lifting when processing in-game logic.
As game codebases grow more complex, reviewing code and fixing errors is a tough task. There are many nooks and crannies in games these days, and locating the source of an error is close to impossible, given the vast areas developers have to search.
AI is being used to conduct code tests quickly and isolate errors and potential breaks in code. These days, games are platform-agnostic. An error on desktop might not show up on mobile or vice-versa. Isolating platform-specific errors is a tough task, and AI is coming to the rescue.
Gaming analytics powered by AI isolate incidents and prevent faulty code releases. This gives developers timely alerts to act upon, and prevent major flaws in their releases.
AI is quickly becoming a central piece of game development as technology improves. Undoubtedly, we will see a wider range of applications in the future as games reach greater levels of sophistication.
