暂无分享,去创建一个
Jun Zhu | Tim Pearce | Jun Zhu | Tim Pearce
[1] Taylor Stanton Hardenstein. "Skins" in the Game: Counter-Strike, Esports, and the Shady World of Online Gambling , 2017 .
[2] Guy Lever,et al. Human-level performance in 3D multiplayer games with population-based reinforcement learning , 2018, Science.
[3] Dmitry I. Ignatov,et al. Predicting Winning Team and Probabilistic Ratings in "Dota 2" and "Counter-Strike: Global Offensive" Video Games , 2017, AIST.
[4] Kristoffer Sjöö,et al. Imitation Learning with Concurrent Actions in 3D Games , 2018, 2018 IEEE Conference on Computational Intelligence and Games (CIG).
[5] Mohammad Norouzi,et al. An Optimistic Perspective on Offline Reinforcement Learning , 2020, ICML.
[6] Hang Su,et al. Playing FPS Games With Environment-Aware Hierarchical Reinforcement Learning , 2019, IJCAI.
[7] Zhao Chen,et al. The Game Imitation: Deep Supervised Convolutional Networks for Quick Video Game AI , 2017, ArXiv.
[8] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[9] Jonathan Lee,et al. Iterative Noise Injection for Scalable Imitation Learning , 2017, ArXiv.
[10] Peter Bakker,et al. Robot see, robot do: An overview of robot imitation , 1996 .
[11] Jakub W. Pachocki,et al. Dota 2 with Large Scale Deep Reinforcement Learning , 2019, ArXiv.
[12] Guillaume Lample,et al. Playing FPS Games with Deep Reinforcement Learning , 2016, AAAI.
[13] Geoffrey J. Gordon,et al. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning , 2010, AISTATS.
[14] Stefan Schaal,et al. Learning from Demonstration , 1996, NIPS.
[15] S. Levine,et al. Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems , 2020, ArXiv.
[16] Sergey Levine,et al. Causal Confusion in Imitation Learning , 2019, NeurIPS.
[17] Bernard Gorman. IMITATIVE LEARNING OF COMBAT BEHAVIOURS IN FIRST-PERSON COMPUTER GAMES , 2007 .
[18] Justin Fu,et al. Datasets for Data-Driven Reinforcement Learning , 2020 .
[19] Junxiao Song,et al. SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II , 2020, ICML.
[20] Tom Schaul,et al. Deep Q-learning From Demonstrations , 2017, AAAI.
[21] Ville Hautamäki,et al. Benchmarking End-to-End Behavioural Cloning on Video Games , 2020, 2020 IEEE Conference on Games (CoG).
[22] Dit-Yan Yeung,et al. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.
[23] Wojciech Jaskowski,et al. ViZDoom: A Doom-based AI research platform for visual reinforcement learning , 2016, 2016 IEEE Conference on Computational Intelligence and Games (CIG).
[24] Santiago Ontañón,et al. A Dynamic-Bayesian Network framework for modeling and evaluating learning from observation , 2014, Expert Syst. Appl..
[25] Vadim Bulitko,et al. An evaluation of models for predicting opponent positions in first-person shooter video games , 2008, 2008 IEEE Symposium On Computational Intelligence and Games.
[26] Ting Chen,et al. Combo-Action: Training Agent For FPS Game with Auxiliary Tasks , 2019, AAAI.
[27] Ruslan Salakhutdinov,et al. MineRL: A Large-Scale Dataset of Minecraft Demonstrations , 2019, IJCAI.
[28] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[29] Wojciech M. Czarnecki,et al. Grandmaster level in StarCraft II using multi-agent reinforcement learning , 2019, Nature.
[30] Marek Wydmuch,et al. ViZDoom Competitions: Playing Doom From Pixels , 2018, IEEE Transactions on Games.
[31] Nicole C. Krämer,et al. Underlying factors of social capital acquisition in the context of online-gaming: Comparing World of Warcraft and Counter-Strike , 2014, Comput. Hum. Behav..
[32] Quoc V. Le,et al. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks , 2019, ICML.