Augmenting Automated Game Testing with Deep Reinforcement Learning
Testing of games is generally a slow and expensive process that become more and more crucial as game grows in size and complexity. Previous standard approaches includes scripting of bots to automatically play and explore the game. This approach is effective in certain areas but lacks the dynamics and learnability to fully test modern AAA games. Therefore, we at SEED and EA are looking into how we can use ML as a tool to further extend that capacity. In this talk we describe our efforts at SEED and EA to use machine learning, specifically reinforcement learning, to improve automated testing of games.
SEED is an advanced R&D group at Electronic Arts. Our goal is to explore the future of game and game creation.
Linus Gisslén is a Senior Research Engineer in Machine Learning at SEED. SEED is an advanced R&D group at Electronic Arts (EA). His current research focus is on Reinforcement Learning (RL) and Procedural Generated Content (PCG). He is the project lead on their effort to use machine learning to improve automated testing of games. Previous experience includes a PhD. from TU München, Germany, and a PostDoc position at Jürgen Schmidhuber's AI lab in Switzerland where the main research focus was on Reinforcement Learning.