AlphaGo - The Movie | Full award-winning documentary
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Further reading 3
Where does AlphaGo get experience? →Describe the task, experience and performance measure before examining the algorithm. AlphaGo provides distinct examples of experience from human games and self-play.How do game agents improve beyond their starting point? →AlphaGo imitates games and then plays against itself. MarI/O selects and reproduces networks according to game progress.Where do strategies absent from demonstrations come from? →Compare self-play in Go with exploration in language-model problem solving. Trial and error can find new strategies when feedback distinguishes useful attempts.
Caption notes
Follow AlphaGo from tests with Fan Hui to its match with Lee Sedol. The film shows how expert games, self-play and search meet the realities of tournament play.
Original passages · 5
AlphaGo tries to maximize
its probability of winning, but it doesn't care at all about
the margin by which it wins.through self-playing,
reinforcement learning, it plays against different versions
of itself many millions of times,It's unbelievably superhuman, in general, but it has some particular weaknesses
in some situations.through self-playing, reinforcement learning, it plays against different versions of itselfcame up with something new, and creative, and different