Well, we don't actually know AlphaGo's true strength in Ko matches because the Ko setup wasn't that complex. There wasn't a lot of trade points available.
A possible explanation is:
During self reinforcement learning, AlphaGo learned to minimize Ko potential by maximizing its probability of winning through diminished available Ko moves.
It would be interesting to see how AlphaGo would be able to capitalize on a game that emphasized Ko play, but that would take more time with AlphaGo to emphasize that kind of play.
edit: I'm not sure why, but I think Lee Sedol is partly holding back, or not playing at his maximum ability. It feels like these games are more along the lines of query games.
I look forward to the next two games because I'm 100% certain Lee Sedol is going to query the AI with some new queries.
A possible explanation is:
During self reinforcement learning, AlphaGo learned to minimize Ko potential by maximizing its probability of winning through diminished available Ko moves.
It would be interesting to see how AlphaGo would be able to capitalize on a game that emphasized Ko play, but that would take more time with AlphaGo to emphasize that kind of play.
edit: I'm not sure why, but I think Lee Sedol is partly holding back, or not playing at his maximum ability. It feels like these games are more along the lines of query games.
I look forward to the next two games because I'm 100% certain Lee Sedol is going to query the AI with some new queries.