When you played through Super Mario Bros. or Doom for the very first time, chances are you didn't try to speedrun the entire game but instead started exploring -- this despite not really knowing what to expect around the next corner. It's that same sense of curiosity, the desire to screw around in a digital landscape just to see what happens, that a team of researchers at UC Berkeley have imparted into their computer algorithm. And it could drastically advance the field of artificial intelligence. Google's AlphaGo AI, the one that just repeatedly dominated the world's top Go players, uses what's called a Monte Carlo tree search function to decide its next move. Each "branch", or decision, in that tree has a weighted value that's determined from previous experiences and the relative rewards associated with them.