SEED Research & Announcements Blogs Publications Open Source Careers Contact Us Research & Announcements Blogs Publications Open Source Careers Contact Us

Self-Learning Agents Play Battlefield 1

Deep Learning

In previous work we used reinforcement learning with concurrent actions combined with imitation learning to improve the training of self-learning agents in 3D environments.

To test the applicability of this methodology in a real-world setting (or at least in a real virtual setting) we initiated a collaboration with DICE with the goal to play the basics of Battlefield 1 using self-learning agents. The results of the collaboration are described in this video:

Related News

A Theory of Stabilization by Skull Carving

SEED
Dec 3, 2024
A new approach to stabilizing facial motion for creating photo-real avatars that significantly enhances accuracy and robustness.

Gigi Lightning Talks

SEED
Sep 26, 2024
SEED brought together developers to show off their prowess using the Gigi rapid prototyping platform for real-time rendering.

SEED's Adventure in Gameplay Innovation

SEED
Sep 13, 2024
SEED is branching out into the world of game mechanics, storytelling magic, and interactive wonders.