arXiv (Cornell University) · 2019 · 1K citations · 33 references
ComputingComputer ScienceArtificial IntelligenceDistributed SystemsMachine LearningContinual LearningDeep LearningGame-based LearningPolicy LearningReinforcement LearningBatch Reinforcement LearningContinual Reinforcement LearningDeep Reinforcement LearningGame-playing AgentsImperfect Information GamesLearning With Imperfect InformationRobustness Of Ai SystemsSelf-play Learning
Dota 2 poses long‑horizon, imperfect‑information, and complex continuous state‑action challenges that are increasingly central to advanced AI systems. OpenAI Five trained via self‑play reinforcement learning on a distributed system, processing about 2 million frames every two seconds and running for ten months. By defeating the world‑champion team OG, OpenAI Five demonstrates that self‑play reinforcement learning can achieve superhuman performance in a complex esports game.
On April 13th, 2019, OpenAI Five became the first AI system to defeat the world champions at an esports game. The game of Dota 2 presents novel challenges for AI systems such as long time horizons, imperfect information, and complex, continuous state-action spaces, all challenges which will become increasingly central to more capable AI systems. OpenAI Five leveraged existing reinforcement learning techniques, scaled to learn from batches of approximately 2 million frames every 2 seconds. We developed a distributed training system and tools for continual training which allowed us to train OpenAI Five for 10 months. By defeating the Dota 2 world champion (Team OG), OpenAI Five demonstrates that self-play reinforcement learning can achieve superhuman performance on a difficult task.
33
Mastering the game of Go with deep neural networks and tree search
David Silver, Aja Huang, Chris J. Maddison et al. · Nature · 2016 · 15.8K citations
Mastering the game of Go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan et al. · Nature · 2017 · 9.2K citations
Engineering, Educational Psychology, Cognitive Psychology +7
Learning to Forget: Continual Prediction with LSTM
Felix A. Gers, Jürgen Schmidhuber, Fred Cummins · Neural Computation · 2000 · 5.4K citations
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver et al. · arXiv (Cornell University) · 2013 · 5.1K citations · Full text