🔥DeepMind’s AlphaStar beats top human players at strategy game StarCraft II
AlphaStar by Google’s DeepMind can now play StarCraft 2 so well that it places in the 99.8 percentile on the European server. In other words, way better than even great human players, achieving performance similar to gods of StarCraft.
Solution basically combines reinforcement learning with a quality-diversity algorithm, which is similar to an evolutionary algorithm.
What’s difficult about StarCraft and how is it different to recent #Go and #Chess AI solutions: even finding winning strategy (StarCraft is famouse to closeness to rock-scissors-paper, not-so-transitive game design, as chess and go), is not enough to win, since the result depends on execution on different macro and micro levels at different timescales.
How that is applicable in real world: basically, it is running logistics, manufacture, research with complex operations and different units.
Why this matters: it brings AI one step closer to running real business.
Blog post: https://deepmind.com/blog/article/AlphaStar-Grandmaster-level-in-StarCraft-II-using-multi-agent-reinforcement-learning
Nature: https://www.nature.com/articles/d41586-019-03298-6
ArXiV: https://arxiv.org/abs/1902.01724
Nontechnical video: https://www.youtube.com/watch?v=6eiErYh_FeY
#Google #GoogleAI #AlphaStar #Starcraft #Deepmind #nature #AlphaZero
AlphaStar by Google’s DeepMind can now play StarCraft 2 so well that it places in the 99.8 percentile on the European server. In other words, way better than even great human players, achieving performance similar to gods of StarCraft.
Solution basically combines reinforcement learning with a quality-diversity algorithm, which is similar to an evolutionary algorithm.
What’s difficult about StarCraft and how is it different to recent #Go and #Chess AI solutions: even finding winning strategy (StarCraft is famouse to closeness to rock-scissors-paper, not-so-transitive game design, as chess and go), is not enough to win, since the result depends on execution on different macro and micro levels at different timescales.
How that is applicable in real world: basically, it is running logistics, manufacture, research with complex operations and different units.
Why this matters: it brings AI one step closer to running real business.
Blog post: https://deepmind.com/blog/article/AlphaStar-Grandmaster-level-in-StarCraft-II-using-multi-agent-reinforcement-learning
Nature: https://www.nature.com/articles/d41586-019-03298-6
ArXiV: https://arxiv.org/abs/1902.01724
Nontechnical video: https://www.youtube.com/watch?v=6eiErYh_FeY
#Google #GoogleAI #AlphaStar #Starcraft #Deepmind #nature #AlphaZero
YouTube
The AI that mastered Starcraft II
Google’s DeepMind artificial intelligence researchers have already mastered games like Pong, Chess and Go but their latest triumph is on another planet. AlphaStar is an artificial intelligence trained to play the science fiction video game StarCraft II.
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Acquisition of Chess Knowledge in AlphaZero
69-pages paper of analysis how #AlphaZero plays chess. TLDR: lots of concepts self-learned by neural network can be mapped to human concepts.
This means that generally speaking we can train neural networks to do some task and then learn something from them. Opposite is also true: we might imagine teaching neural networks some human concepts in order to maek them more efficient.
Post: https://en.chessbase.com/post/acquisition-of-chess-knowledge-in-alphazero
Paper: https://arxiv.org/pdf/2111.09259.pdf
#RL
69-pages paper of analysis how #AlphaZero plays chess. TLDR: lots of concepts self-learned by neural network can be mapped to human concepts.
This means that generally speaking we can train neural networks to do some task and then learn something from them. Opposite is also true: we might imagine teaching neural networks some human concepts in order to maek them more efficient.
Post: https://en.chessbase.com/post/acquisition-of-chess-knowledge-in-alphazero
Paper: https://arxiv.org/pdf/2111.09259.pdf
#RL
Chess News
Acquisition of Chess Knowledge in AlphaZero
Researchers at DeepMind and Google Brain, in collaboration with Grandmaster Vladimir Kramnik, are working to explore what chess can teach us about AI and vice versa. Using Chessbase’s extensive historical chess data along with the AlphaZero neural network…