Electronic Arts' experimental SEED division is currently using machine learning to help streamline game testing and simulator human behavior.
EA's games are getting bigger and bigger. Battlefield 2042, for example, is always-online and features 128-player multiplayer. It's the biggest project DICE has ever done. To make the game a reality, EA and DICE have used machine learning and AI to help initiate deep testing that goes beyond human capabilities.
In an i3D 2021 presentation from April, EA SEED Head of Technology Colin Barre-Brisebois talked about how the R&D division is using machine learning and AI to help optimize game development, testing, and content deployment.
It is well known that games are getting bigger and bigger, and that with games running as a live-service, that gamers want more content, delivered faster. And this is where Machine Learning comes in and enables us to improve how we test these games at scale and speed, so that we can deliver better content faster and hopefully bug free.
Instead of taking a brute force approach of just throwing people at the problem, we use machine learning to build tools that help our tester's with tedious tasks, which means an overall improvement of quality-of-life for our developers, where they can focus on more important and fundamental testing.
Also, with neural networks learning how to play the games by themselves we can mimic human-like behaviors that go beyond current automated testing approaches, of scripted bots, where the game learns and plays like a human. This means we find bugs faster, in ways that humans do, before they get out in the wild to millions of players.
This sounds exactly like the kind of thing DICE uses in Battlefield 2042 to enable its advanced AI bots to populate its servers for 24/7 Battlefield mayhem.
The ML tech will also be used for live games like EA Sports titles like Madden NFL and FIFA, both of which are pushing advanced new systems and technologies on PlayStation 5 and Xbox Series X/S consoles.
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