The Reinforcement-Learning Methods that Allow AlphaStar to Outcompete Almost All Human Players at StarCraft II - KDnuggets

In January, artificial intelligence(AI) powerhouse DeepMind announced it had achieved a major milestone in its journey towards building AI systems that resemble human cognition. AlphaStar was a DeepMind agent designed using reinforcement learning that was able to beat two professional players at a game of StarCraft II, one of the most complex real-time strategy games of all time. During the last few months, DeepMind continued evolving AlphaStar to the point that the AI agent is now able to play a full game of StarCraft II at a Grandmaster level outranking 99.8% of human players. The results were recently published in Nature and they show some of the most advanced self-learning techniques used in modern AI systems. DeepMind's milestone is better explained by illustrating the trajectory from the first version of AlphaStar to the current one as well as some of the key challenges of StarCraft II.