In an old school gaming party to end all parties, Google's new deep Q-network (DQN) algorithm is likely to mop the floor with you at Breakout or Space Invaders, but maybe take a licking at Centipede. Provided with only the same inputs as a human player and no previous real-world knowledge, DQN uses reinforcement learning to learn new games, and in some cases, develop new strategies. Its designers argue that this kind of general learning algorithm can crossover into discovery making in other fields. .. Continue Reading Google's deep Q-network proves a quick study in classic Atari 2600 games
Section: Computers
Tags: Artificial Intelligence, Games, Google, Learning, Video Games
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