Grandmaster level in StarCraft II using multi-agent reinforcement learning
This is a really interesting one to digest. As with previous announcements about AlphaStar, much of the feedback (here and elsewhere) is about the fundamental challenge of assessing human vs. machine in an RTS. These points are very valid - stepping back however, this still feels like a pretty incredible accomplishment.<p>I&#x27;m a gold league SC2 player, so maybe in the 30th-50th percentile. Three years ago, when DeepMind started this project (and after nearly two decades of research into SC&#x2F;SC2) I could probably have beaten the best non-cheating AI. Now, after 3 years, this AI is playing at a Grandmaster level, under at least a reasonable approach to fairness. By comparison, according to the AlphaGo paper [1] the best Go AIs prior to AlphaGo were playing at a 6 Dan level, which looks to be somewhere in the 90-98th percentile [2].<p>The speed at which AlphaStar overtook previous AIs seems to me to be nearly unprecedented in AI research. This is like if the world&#x27;s best chess AI had gone from losing high school tournaments to being competitive with Kasparov in less than 3 years. Valid criticisms aside, this feels like an incredible achievement.<p>[1] <a href="https:&#x2F;&#x2F;www.nature.com&#x2F;articles&#x2F;nature16961.pdf" rel="nofollow">https:&#x2F;&#x2F;www.nature.com&#x2F;articles&#x2F;nature16961.pdf</a>
[2] <a href="https:&#x2F;&#x2F;senseis.xmp.net&#x2F;?KGSRankHistogram" rel="nofollow">https:&#x2F;&#x2F;senseis.xmp.net&#x2F;?KGSRankHistogram</a>