do you understand the difference between human learning and machine learning?
I was thinking about this. I've personally have played many strategy games, particularly trading card games (I've played so far Yugioh!, Magic, Pokemon, and a bunch of lesser known games ) and I was thinking how I learned to play them.
The first thing of course it to keep the rules of the game in mind, how to play it, how to win and the such. I think that's the easiest part. The hard part is to learn the so-called "unspoken rules", those are more like guides instead of rules but if you follow them you can increase your chances of winning. Unspoken rules usually involve particular card combinations, or certain general strategies. And those are the ones you learn by seeing how others play and by practice.
As you start practicing and seeing you start learning the unspoken rules. So if I play a lot, and I get my ass handed to me because the dude uses a particular card strategy, I add to my mind the rule "when playing use this and that card strategy". Of course, then I use it and someone developed a counter-strategy to that card stategy and so the rule becomes more complex like "when playing use this and that card strategy except when my oponent has this counter-strategy in which case use this and that card strategy". And so on and so forth.
I've also played against computers in the past, old programs from the 90s or mid 2000. They are quite easy to beat because they never learn, you can beat them over and over again using the same dumb strategies and the program will never catch the unspoken rule. it sometimes gets annoying because it's like playing with a stubborn child that just refuses to accept that he should change the focus of it's strategy.
Reading the thread, it seems the machine is an advancement from this old programs. The programmers only gave the written rules of Go, and the machine learned through observation the unwritten ones, so it's constantly changing. You may beat it the first time in a way, but it will probably not fall for the same trick twice.