"I feel like most pros would have lost all these stalkers by now," he added.ĪlphaStar's performance was particularly impressive, because at some points he was using this tactic with multiple groups of Stalkers in different locations. AlphaStar would attack Komincz's units and "then blink away" before taking significant damage. "We keep seeing AlphaStar do that trick that you're talking about," said commentator Dan Stemkoski. And that can get tricky, because a StarCraft player often has a lot of other stuff on his plate-he needs to worry about building new units in his base, scouting for enemy bases, watching for enemy attacks, and so forth.Ĭommentators watching the climactic Game 4 battle between AlphaStar and Komincz marveled at AlphaStar's micro abilities. The player needs to monitor the health of Stalkers to figure out which ones need to blink away. The downside of this approach is that it demands constant player attention. Stalker shields gradually recharge, so by continuously rotating their troops, AlphaStar was able to do a lot of damage to the enemy while losing very few of its own units. That created an opportunity for AlphaStar: it could attack with a big group of Stalkers, have the front row of stalkers take some damage, and then blink them to the rear of the army before they got killed. The climactic battle of the game pitted a Komincz army composed of several different unit types (mostly Immortals, Archons, and Zealots) against an AlphaStar army composed entirely of Stalkers.
Starcraft 2 game crashes every match series#
This ability was most obvious in Game 4 of AlphaStar's series against Komincz. Komincz was the stronger of the two human players AlphaStar faced, and Game 4 was the closest Komincz came to winning during the five-game series. The commentators were blown away by AlphaStar's "micro" capabilities-the ability to make quick tactical decisions in the heat of battle.
Starcraft 2 game crashes every match professional#
Last week DeepMind invited two professional StarCraft players and announcers to provide commentary as they replayed some of AlphaStar's 10 games against Wünsch and Komincz. AlphaStar had an unfair advantage in its initial games One consequence of this approach was that the human players faced a different opposing strategy in each game they played against AlphaStar. DeepMind says that this initial agent "defeated the built-in Elite level AI-around gold level for a human player-in 95% of games." AdvertisementĪt the end of this process, DeepMind selected five of the strongest agents from its virtual menagerie to face off against AlphaStar's human challengers. This reinforcement learning technique was sufficient to build a competent StarCraft II bot. The process started by using supervised learning to help agents learn to mimic the strategies of human players. But DeepMind does explain in some detail how it trained its virtual StarCraft players to get better over time. DeepMind declined to talk to me for this story, and DeepMind has yet to release a forthcoming peer-reviewed paper explaining exactly how AlphaStar works. I'll cop to not fully understanding what all of that means. More specifically, the neural network architecture applies a transformer torso to the units, combined with a deep LSTM core, an auto-regressive policy head with a pointer network, and a centralized value baseline."
AlphaStar was trained using "up to 200 years" of virtual gameplayĭeepMind writes that "AlphaStar’s behavior is generated by a deep neural network that receives input data from the raw game interface (a list of units and their properties) and outputs a sequence of instructions that constitute an action within the game. But it wasn't quite as big of an accomplishment as it might appear at first glance because it wasn't an entirely fair fight. AlphaStar won a five-game series against Wünsch 5-0, then beat Komincz 5-0, too.ĪlphaStar may be the strongest StarCraft AI ever created. The company pitted its AI, dubbed AlphaStar, against two top StarCraft players-Dario "TLO" Wünsch and Grzegorz "MaNa" Komincz. Last Thursday, DeepMind announced a significant breakthrough. DeepMind says that prior to its own effort, no one had come close to designing a StarCraft AI as good as the best human players.
StarCraft is particularly challenging for an AI because players must carry out long-term plans over several minutes of gameplay, tweaking them on the fly in the face of enemy counterattacks. StarCraft requires players to gather resources, build dozens of military units, and use them to try to destroy their opponents. Specifically, DeepMind decided to write an AI to play the realtime strategy game StarCraft II. So what do you do after mastering one of the world's most challenging board games? You tackle a complex video game. DeepMind, the AI startup Google acquired in 2014, is probably best known for creating the first AI to beat a world champion at Go.
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