arXiv:2108.03452
공식 코드 · Papers with Code
Rethinking of AlphaStar
원문 초록
We present a different view for AlphaStar (AS), the program achieving Grand-Master level in the game StarCraft II. It is considered big progress for AI research. However, in this paper, we present problems with the AS, some of which are the defects of it, and some of which are important details that are neglected in its article. These problems arise two questions. One is that what can we get from the built of AS? The other is that does the battle between it with humans fair? After the discussion, we present the future research directions for these problems. Our study is based on a reproduction code of the AS, and the codes are available online.
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AVA: Attentive VLM Agent for Mastering StarCraft II
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning
Hierarchical Expert Prompt for Large-Language-Model: An Approach Defeat Elite AI in TextStarCraft II for the First Time
Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination Dynamics
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement Learning
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