StarCraft II Build Order Optimization using Deep Reinforcement Learning and Monte-Carlo Tree Search

12 Jun 2020Islam ElnabarawyKristijana ArroyoDonald C. Wunsch II

The real-time strategy game of StarCraft II has been posed as a challenge for reinforcement learning by Google's DeepMind. This study examines the use of an agent based on the Monte-Carlo Tree Search algorithm for optimizing the build order in StarCraft II, and discusses how its performance can be improved even further by combining it with a deep reinforcement learning neural network... (read more)

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