State Estimation Archives

How does AlphaStar handle the challenge of partial observability in StarCraft II, and what strategies does it use to gather information and make decisions under uncertainty?

Tuesday, 11 June 2024 by EITCA Academy

AlphaStar, developed by DeepMind, represents a significant advancement in the field of artificial intelligence, particularly within the domain of reinforcement learning as applied to complex real-time strategy games such as StarCraft II. One of the primary challenges AlphaStar faces is the issue of partial observability inherent to the game environment. In StarCraft II, players do

Published in Artificial Intelligence, EITC/AI/ARL Advanced Reinforcement Learning, Case studies, AplhaStar mastering StartCraft II, Examination review

Tagged under: Artificial Intelligence, DeepMind, Game Theory, Imitation Learning, LSTM, Multi-Agent Training, Reinforcement Learning, RNN, Scouting, StarCraft II, State Estimation

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How does AlphaStar handle the challenge of partial observability in StarCraft II, and what strategies does it use to gather information and make decisions under uncertainty?

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How does AlphaStar handle the challenge of partial observability in StarCraft II, and what strategies does it use to gather information and make decisions under uncertainty?

Eligibility for EITCA Academy 80% EITCI DSJC Subsidy support