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Deep reinforcement learning (RL) has shown impressive results in a variety of domains, learning directly from high-dimensional sensory streams.
Incremental evolution of complex general behavior
F. Gomez and R. Miikkulainen · 1997
Earlier work this paper cites.
Evolving robust and specialized car racing skills
J. Togelius and S. M. Lucas · 2006
Earlier work this paper cites.
Curriculum learning
Y. Bengio, J. Louradour, R. Collobert, and J. Weston · 2009
Earlier work this paper cites.
Cellular automata for real-time generation of infinite cave levels
L. Johnson, G. N. Yannakakis, and J. Togelius · 2010
Earlier work this paper cites.
The arcade learning environment: An evaluation platform for general agents
M. G. Bellemare, Y. Naddaf, J. Veness, and M. Bowling · 2013
Earlier work this paper cites.
Towards a video game description language
M. Ebner, J. Levine, S. M. Lucas, T. Schaul, T. Thompson, and J. Togelius · 2013
Earlier work this paper cites.
A video game description language for model-based or interactive learning
T. Schaul · 2013
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Powerplay: Training an increasingly general problem solver by continually searching for the simplest still unsolvable problem
J. Schmidhuber · 2013
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The Mario AI championship 2009-2012
J. Togelius, N. Shaker, S. Karakovskiy, and G. N. Yannakakis · 2013
Earlier work this paper cites.
Mazes for Programmers: Code Your Own Twisty Little Passages
J. Buck · 2015
Earlier work this paper cites.
C. Beattie, J. Z. Leibo, D. Teplyashin, T. Ward, M. Wainwright, H. Küttler, A. Lefrancq, S. Green, V. Valdés, A. Sadik, et al · 2016
Earlier work this paper cites.
Matching games and algorithms for general video game playing
P. Bontrager, A. Khalifa, A. Mendes, and J. Togelius · 2016
Earlier work this paper cites.
G. Brockman, V. Cheung, L. Pettersson, J. Schneider, J. Schulman, J. Tang, and W. Zaremba · 2016
Earlier work this paper cites.
Hybrid computing using a neural network with dynamic external memory
A. Graves, G. Wayne, M. Reynolds, T. Harley, I. Danihelka, A. Grabska-Barwińska, S. G. Colmenarejo, E. Grefenstette, T. Ramalho, J. Agapiou, et al · 2016
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ViZDoom: A Doom-based AI research platform for visual reinforcement learning
M. Kempka, M. Wydmuch, G. Runc, J. Toczek, and W. Jaśkowski · 2016
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Bipedalwalkerhardcore-v2
O. Klimov · 2016
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Asynchronous methods for deep reinforcement learning
V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu · 2016
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General Video Game AI: Competition, Challenges and Opportunities
D. Perez-Liebana, S. Samothrakis, J. Togelius, S. M. Lucas, and T. Schaul · 2016
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Learning generalized reactive policies using deep neural networks
E. Groshev, M. Goldstein, A. Tamar, S. Srivastava, and P. Abbeel · 2017
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Deep learning for video game playing
N. Justesen, P. Bontrager, J. Togelius, and S. Risi · 2017
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Schema networks: Zero-shot transfer with a generative causal model of intuitive physics
K. Kansky, T. Silver, D. A. Mély, M. Eldawy, M. Lázaro-Gredilla, X. Lou, N. Dorfman, S. Sidor, S. Phoenix, and D. George · 2017
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Teacher-student curriculum learning
T. Matiisen, A. Oliver, T. Cohen, and J. Schulman · 2017
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Intrinsic motivation and automatic curricula via asymmetric self-play
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S. Ruder · 2016
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Cad2rl: Real single-image flight without a single real image
F. Sadeghi and S. Levine · 2016
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Procedural content generation in games
N. Shaker, J. Togelius, and M. J. Nelson · 2016
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Hindsight experience replay
M. Andrychowicz, F. Wolski, A. Ray, J. Schneider, R. Fong, P. Welinder, B. McGrew, J. Tobin, P. Abbeel, and W. Zaremba · 2017
Cited alongside, same era.
Minimal criterion coevolution: a new approach to open-ended search
J. C. Brant and K. O. Stanley · 2017
Cited alongside, same era.
Openai baselines
P. Dhariwal, C. Hesse, O. Klimov, A. Nichol, M. Plappert, A. Radford, J. Schulman, S. Sidor, and Y. Wu · 2017
Cited alongside, same era.
Reverse curriculum generation for reinforcement learning
C. Florensa, D. Held, M. Wulfmeier, M. Zhang, and P. Abbeel · 2017
Cited alongside, same era.
S. Sukhbaatar, Z. Lin, I. Kostrikov, G. Synnaeve, A. Szlam, and R. Fergus · 2017
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Domain randomization and generative models for robotic grasping
J. Tobin, W. Zaremba, and P. Abbeel · 2017
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Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures
L. Espeholt, H. Soyer, R. Munos, K. Simonyan, V. Mnih, T. Ward, Y. Doron, V. Firoiu, T. Harley, I. Dunning, et al · 2018
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Automated curriculum learning by rewarding temporally rare events
N. Justesen and S. Risi · 2018
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The single-player GVGAI learning framework technical manual
J. Liu, D. Perez-Lebana, and S. M. Lucas · 2018
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D. Perez-Liebana, J. Liu, A. Khalifa, R. D. Gaina, J. Togelius, and S. M. Lucas · 2018
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Deep reinforcement learning for general video game AI
R. Rodriguez Torrado, P. Bontrager, J. Togelius, J. Liu, and D. Perez-Liebana · 2018
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Evolving mario levels in the latent space of a deep convolutional generative adversarial network
V. Volz, J. Schrum, J. Liu, S. M. Lucas, A. Smith, and S. Risi · 2018
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A study on overfitting in deep reinforcement learning
C. Zhang, O. Vinyals, R. Munos, and S. Bengio · 2018
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