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How Google Deepmind's Ant Soccer Skills Can Help Improve Your Search Results

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Live-action ant soccer.

Google's DeepMind artificial intelligence is taking on new 3D navigation and puzzle-solving games, including ant soccer, in which it has learned how to chase down a ball, dribble, and then score a goal.

Credit: Andrey Pavlov/Caters News

Google's DeepMind artificial intelligence (AI) is learning to navigate thee-dimensional (3D) environments and puzzle-solving games, including a soccer game in which the AI plays as a virtual ant, according to DeepMind's David Silver.

Silver says the AI controls the ant's four-legged movement to chase down the virtual soccer ball, dribble, and score a goal; previously, the AI mastered two-dimensional Atari games. The ant soccer challenge was solved via reinforcement learning and DeepMind's Deep-Q Network algorithm, which stores a bot's experiences and estimates actionable rewards.

DeepMind also developed an asynchronous actor-critic algorithm, called A3C, to help the AI learn how to play soccer without prior experiences. Silver says A3C uses standard multicore central-processing units instead of graphics processing unit-based algorithms to solve motor-control challenges and 3D navigation using visual input in a fraction of the training time.

He also notes DeepMind is testing its AI with Labyrinth, a 3D maze and puzzle game using only visual cues.

DeepMind also has created Gorila, a reinforcement learning system with quick training times, which has been applied to Google recommender systems, according to Silver.

From ZDNet
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