You've been logged out of GDC Vault since the maximum users allowed for this account has been reached. To access Members Only content on GDC Vault, please log out of GDC Vault from the computer which last accessed this account.

Click here to find out about GDC Vault Membership options for more users.

close
    
Session Name: Machine Learning Summit: Identify your Players' Builds from In-Game Data: The BaT Approach
Speaker(s): David Renaudie
Company Name(s): Massive Entertainment
Track / Format: Machine Learning Summit
Overview: Understanding the builds effectively used by players in RPG looter online games is key for designers and other stakeholders; but due to combinatorial explosion inherent to the nature of data, traditional unsupervised machine learning approaches often fail at extracting meaningful and actionable results.nnWe propose a novel and original method - called "BaT" - to automatically segment high volumes of player in-game data into meaningful player builds, that produce easily interpretable builds clusters in a fast, efficient, and scalable way.

Game Developers Conference 2021

David Renaudie

Massive Entertainment

free content

Machine Learning Summit

Programming