All About Japan

How to Play Go

| Gaming , Toys

Here’s how a game played out for us on You can choose the board size and whether or not you would like the computer to be handicapped, but the one feature you can't change is your color, as you are always black.

Early in the game, you start by trying to establish your territories. You can already tell which parts of the board black and white are going after...

But to expand your own territory, you need to invade and attack the territory your opponent has formed. You can see the white side attacking us in the bottom right side of the board.

This is where the game starts to get really interesting. You have a series of little battles like these, where you have to count ahead of your opponent and out-maneuver their moves to prevent getting captured or losing territory. Remember, if your stone gets surrounded, it’s essentially “killed.”

The more we played, white took control of most of the board. We tried to attack, as you can see on the upper left side of the board.

That didn’t turn out too well. We ended up taking only a small portion of its land.

It was clear the white side was better. We only managed to take control of about a third of the board (the right side) before we had to call it quits.

In the end, you count the number of squares you have under control to determine the winner. It’s typically hard to know the exact score by just looking at the board during the game.

We doubt the online game we played had any AI capabilities, but it still was able to predict our next move and read certain sequences. It was reading our patterns and had the ability to tell what our next move was likely going to be.

And that’s probably the exact reason why Google’s so obsessed with go—it wants to build a system that’s capable of predicting human behavior.

And as Google gets better at reading and predicting human behavior, it will be able to apply its progress in AI to other areas. According to Brown University computer scientist Michael L. Littman, AlphaGo’s technology could be applied to Google’s self-driving cars, where the AI has to make decisions continuously, or in a problem-solving search capacity, like showing a gluten-free baking recipe.

Google’s ambitions in predicting human behavior are clearly much bigger than just outsmarting the best go player in the world. “Ultimately we want to apply this to big real-world problems,” Hassabis said.

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