Data from game analytics is used to obtain specific information about what a player wants, predicting game issues, consultations, and time.
New game concepts, news stories, and machines are built using previously acquired data.
The gaming industry makes full use of data analytics. Technology, finance, game, marketing, strategy, just say the domain of statistics and you will find it works with the revenue in the gaming industry.
Most of the popular games in the industry are the ‘open-world’ games which allow the player to interact with the environment.
But this universe-creation takes a lot of time to be perfect and consists of repetitive and small tasks.
With the help of Machine Learning, the time taken by the process has reduced manifold and the developers can utilize the time saved in more creative processes.
Generally, the Non-Playable Characters have to be hard-encoded in the sense that they are scripted characters which respond to
fixed situations with a fixed set actions. With the incorporation of Machine Learning, these characters can adapt according to the environment
and the player’s game-style.
For example, in the game Metal Gear Solid 5: The Phantom Pain produced by Kojima Productions, if a player continuously uses the technique of headshots in the game, the characters adapt to it by starting to “wear” helmets to prevent getting hit on the head.
Typical open-world games require the player to interact with its environments and “fellow-men” to complete the objectives.
With the rise of Natural Language Processing, the player can interact with other characters in a more realistic manner.
For example, in Rockstar Games’ Red Dead Redemption 2, one has to maintain the ‘honor’ level of our character and the other in-game characters interact with the player according to this rating.