Re:Deep Mind Playing Montezuma's Revenge with Intrinsic Moti...
by IanCal on Thursday June 09, 2016 @06:27AM
(#11868497)
I'd be surprised if it isn't, in many ways. Go is highly different from our normal reality so we have to learn how a series of very specific rules interact with each other and learn useful patterns.
Games like Montezuma's Revenge allow us to re-use huge amounts of already known information. We recognise there's a little person, and that's who we're controlling. We have expectations around what a jump might mean and that we probably shouldn't touch the skulls. We expect that moving off the screen to the next room then back goes to the first screen again. The game, in many ways, acts similarly to our normal reality (object persistence, motion, etc). We know we want to survive. We can even read the text on the screen and focus on increasing the numbers.
The AI has just has pixel values, and none of this information. It doesn't know about jumping, reality or skulls. It has a grayscale 42x42 view of something and is given a few ways of poking this world.
Edit - Perhaps another way of looking at it is this:
In go, you have 19x19 positions which can be in one of just 3 states. You must choose a move to make out of a large number of possibilities. This is repeated and the world changes very slowly.
In this game, you have 42x42 positions which can each be in a much larger number of possible states (somewhere between 8 and 128 I think). You have only a few possible moves but the world changes rapidly and sometimes completely. The interactions between the way the world changes in response to your actions are significantly more complicated.
Games like Montezuma's Revenge allow us to re-use huge amounts of already known information. We recognise there's a little person, and that's who we're controlling. We have expectations around what a jump might mean and that we probably shouldn't touch the skulls. We expect that moving off the screen to the next room then back goes to the first screen again. The game, in many ways, acts similarly to our normal reality (object persistence, motion, etc). We know we want to survive. We can even read the text on the screen and focus on increasing the numbers.
The AI has just has pixel values, and none of this information. It doesn't know about jumping, reality or skulls. It has a grayscale 42x42 view of something and is given a few ways of poking this world.
Edit - Perhaps another way of looking at it is this:
In go, you have 19x19 positions which can be in one of just 3 states. You must choose a move to make out of a large number of possibilities. This is repeated and the world changes very slowly.
In this game, you have 42x42 positions which can each be in a much larger number of possible states (somewhere between 8 and 128 I think). You have only a few possible moves but the world changes rapidly and sometimes completely. The interactions between the way the world changes in response to your actions are significantly more complicated.