ViZDoom in Research

Autoencoder-augmented Neuroevolution for Visual Doom Playing, Samuel Alvernaz, Julian Togelius (arXiv:1707.03902)

Curiosity-driven Exploration by Self-supervised Prediction, Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell (arXiv:1705.05363)

Learning to Act by Predicting the Future, Alexey Dosovitskiy, Vladlen Koltun (learning-to-act.pdf)

Training Agent for First-Person Shooter Game with Actor-Critic Curriculum Learning, Yuxin Wu, Yuandong Tian, Published as a conference paper at ICLR 2017 (openreview)

Arnold: An Autonomous Agent to play FPS Games, Devendra Singh Chaplot, Guillaume Lample, 2016 (arnold_aaai17.pdf)

Playing Doom with SLAM-Augmented Deep Reinforcement Learning, Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N. Siddharth, Philip H. S. Torr, 2016 (arXiv:1612.003801)

Playing FPS Games with Deep Reinforcement Learning, Guillaume Lample, Devendra Singh Chaplot, 2016 (arXiv:1609.05521)

Deep Successor Reinforcement Learning, Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman, 2016 (arXiv:1606.02396)

OpenAI Gym, Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, Wojciech Zaremba, 2016 (arXiv:1606.01540)

ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning, Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Toczek & Wojciech Jaśkowski, 2016 (arXiv:1605.02097)