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AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning
This paper introduces AlphaStar Unplugged, a benchmark for offline reinforcement learning in the game StarCraft II. It includes a dataset, API tools, evaluation protocol, and baseline agents, achieving a 90% win rate against a previous agent.
https://arxiv.org/abs//2308.03526
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
This paper introduces AlphaStar Unplugged, a benchmark for offline reinforcement learning in the game StarCraft II. It includes a dataset, API tools, evaluation protocol, and baseline agents, achieving a 90% win rate against a previous agent.
https://arxiv.org/abs//2308.03526
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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