Your general sentiment was true with old-school AI that was just exploring trees of options and intelligently pruning branches. However, for quite some time now

Your general sentiment was true with old-school AI that was just exploring trees of options and intelligently pruning branches. However, for quite some time now we've moved beyond that and into areas that are promising for generalization. You may want to explore the work that DeepMind[1] has done. They're starting with simple universes (Atari games), but have developed a single program that can learn to play dozens of different games without having ever been told the rules. They learn by trial and error (specifically, Q-learning[2]) and rely only on reading pixels and knowing the current score. They learn fairly sophisticated behaviors and ultimately learn to play these games at levels far superior to what humans can achieve. Many people are now trying to generalize these results to more realistic worlds, such as 3D games. And ultimately to agents that interact with the real world. [1] http://deepmind.com/ http://deepmind.com/ [2] https://en.wikipedia.org/wiki/Q-learning https://en.wikipedia.org/wiki/Q-learning