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This paper presents the first two editions of Visual Doom AI Competition, held in 2016 and 2017.
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Docker: Lightweight linux containers for consistent development and deployment
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Human-level control through deep reinforcement learning
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Deep attention recurrent q-network
Ivan Sorokin, Alexey Seleznev, Mikhail Pavlov, Aleksandr Fedorov, and Anastasiia Ignateva · 2015
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Charles Beattie, Joel Z. Leibo, Denis Teplyashin, Tom Ward, Marcus Wainwright, Heinrich Küttler, Andrew Lefrancq, Simon Green, Víctor Valdés, Amir Sadik, Julian Schrittwieser, Keith Anderson, Sarah York, Max Cant, Adam Cain, Adrian Bolton, Stephen Gaffney, Helen King, Demis Hassabis, Shane Legg, and Stig Petersen · 2016
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Playing doom with slam-augmented deep reinforcement learning
Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N. Siddharth, and Philip H. S. Torr · 2016
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Transfer deep reinforcement learning in 3d environments: An empirical study
Devendra Singh Chaplot, Guillaume Lample, and Ruslan Salakhutdinov · 2016
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The malmo platform for artificial intelligence experimentation
Matthew Johnson, Katja Hofmann, Tim Hutton, and David Bignell · 2016
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ViZDoom: A Doom-based AI research platform for visual reinforcement learning
Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Toczek, and Wojciech Jaśkowski · 2016
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Playing FPS games with deep reinforcement learning
Guillaume Lample and Devendra Singh Chaplot · 2016
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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General video game ai: Competition, challenges, and opportunities
Diego Perez-Liebana, Spyridon Samothrakis, Julian Togelius, Simon M. Lucas, and Tom Schaul · 2016
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Unrealcv: Connecting computer vision to unreal engine
Weichao Qiu and Alan Yuille · 2016
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Mastering the game of Go with deep neural networks and tree search
David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis · 2016
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How to run a successful game-based ai competition
Julian Togelius · 2016
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Dueling network architectures for deep reinforcement learning
Ziyu Wang, Tom Schaul, Matteo Hessel, Hado Van Hasselt, Marc Lanctot, and Nando De Freitas · 2016
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Ms. pac-man versus ghost team cig 2016 competition
P. R. Williams, D. Perez-Liebana, and S. M. Lucas · 2016
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AI2-THOR: An Interactive 3D Environment for Visual AI
Eric Kolve, Roozbeh Mottaghi, Daniel Gordon, Yuke Zhu, Abhinav Gupta, and Ali Farhadi · 2017
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Neural map: Structured memory for deep reinforcement learning
Emilio Parisotto and Ruslan Salakhutdinov · 2017
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Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, and Trevor Darrell · 2017
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Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adrià Puigdomènech Badia, Oriol Vinyals, Demis Hassabis, Daan Wierstra, and Charles Blundell · 2017
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Unrealcv: Virtual worlds for computer vision
Weichao Qiu, Fangwei Zhong, Yi Zhang, Siyuan Qiao, Zihao Xiao, Tae Soo Kim, Yizhou Wang, and Alan Yuille · 2017
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C. Yan, D. Misra, A. Bennnett, A. Walsman, Y. Bisk, and Y. Artzi · 2016
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Home: a household multimodal environment
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The current state of starcraft ai competitions and bots
Michal Certicky and David Churchill · 2017
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Gated-attention architectures for task-oriented language grounding
Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, and Ruslan Salakhutdinov · 2017
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Learning to act by predicting the future
Alexey Dosovitskiy and Vladlen Koltun · 2017
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Deep recurrent q-learning for partially observable mdps
Matthew J. Hausknecht and Peter Stone · 2017
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Recognition in-the-tail: Training detectors for unusual pedestrians with synthetic imposters
Shiyu Huang and Deva Ramanan · 2017
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Clyde: A deep reinforcement learning doom playing agent
Dino Ratcliffe, Sam Devlin, Udo Kruschwitz, and Luca Citi · 2017
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Mastering chess and shogi by self-play with a general reinforcement learning algorithm
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy P. Lillicrap, Karen Simonyan, and Demis Hassabis · 2017
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Training agent for first-person shooter game with actor-critic curriculum learning
Yuxin Wu and Yuandong Tian · 2017
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The Text-Based Adventure AI Competition
T. Atkinson, H. Baier, T. Copplestone, S. Devlin, and J. Swan · 2018
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Lukasz Kidzinski, Sharada Prasanna Mohanty, Carmichael F. Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis, Zhibo Chen, Zhizheng Zhang, Jiale Chen, Jun Shi, Zhuobin Zheng, Chun Yuan, Zhihui Lin, Henryk Michalewski, Piotr Milos, Blazej Osinski, Andrew Melnik, Malte Schilling, Helge Ritter, Sean F. Carroll, Jennifer L. Hicks, Sergey Levine, Marcel Salathé, and Scott L. Delp · 2018
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Psychlab: A psychology laboratory for deep reinforcement learning agents
Joel Z. Leibo, Cyprien de Masson d’Autume, Daniel Zoran, David Amos, Charles Beattie, Keith Anderson, Antonio García Castañeda, Manuel Sanchez, Simon Green, Audrunas Gruslys, Shane Legg, Demis Hassabis, and Matthew Botvinick · 2018
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Building Generalizable Agents with a Realistic and Rich 3D Environment
Y. Wu, Y. Wu, G. Gkioxari, and Y. Tian · 2018
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