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Seminar: Mikael Kågebäck – Go solved by Google!? How Google Deep Mind were able to beat a professional Go player using deep reinforcement learning

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Last week, 27 Jan 2016, something extraordinary happened. A team of researches from DeepMind, the company that got famous by developing an algorithm that can learn to play Atari games (and being purchased by Google for 400 Million pounds), published a paper in Nature describing a solution to what many consider a milestone towards general artificial intelligence. An algorithm that is able to beat professional players in the board game of Go, a game so complex that any brute force approach is bound to fail miserably. In this talk I will present the results of their paper, how deep neural networks were used together with reinforcement learning and Monte-Carlo tree search to navigate a search space more than one googol (10^100) times larger than chess, and winning 5 out of 5 matches against the european Go champion Fan Hui.

Date: 2016-02-04 10:30 - 12:00

Location: EDIT-room 3364, Chalmers Johanneberg

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Page updated: 2016-02-01 16:41

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