Monto Carlo Tree Search in Real Time Strategy Games with Applications to Starcraft 2
This thesis presents an architecture for an agent that can play the real-time strategy game Starcraft 2 (SC2) by applying Monte Carlo Tree Search (MCTS) together with genetic algorithms and machine learning methods. Together with the MCTS search, a light-weight and accurate combat simulator for SC2...
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Format: | Others |
Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2019
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Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263150 |