Julian Schrittwieser

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The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses 'value networks' to evaluate board positions and 'policy networks' to select moves. These deep neural(More)
DeepMindLab is a first-person 3Dgameplatformdesigned for research and development of general artificial intelligence and machine learning systems. DeepMind Lab can be used to study how autonomous artificial agents may learn complex tasks in large, partially observed, and visually diverse worlds. DeepMindLab has a simple and flexibleAPI enabling creative(More)
This paper introduces SC2LE (StarCraft II Learning Environment), a reinforcement learning environment based on the game StarCraft II. This domain poses a new grand challenge for reinforcement learning, representing a more difficult class of problems than considered in most prior work. It is a multi-agent problem with multiple players interacting; there is(More)
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