The argument breaks down because you are equivocating on what the space is to search over and what the utility function in question is.
Under a given utility function U, “change the utility function to U’ ” won’t generally have positive utility. Self-awareness and pleasure-seeking aren’t some natural properties of optimization processes. They have to be explicitly built in.
Suppose you set a theorem-prover to work looking for a proof of some theorem. It’s searching over the space of proofs. There’s no entry corresponding to “pick a different and easier theorem to prove”, or “stop proving theorems and instead be happy.”
Yes, I just changed the notation to be more standard. The point remains. There need not be any “x” that corresponds to “pick a new r” or to “pretend x was really x’”. If there was such an x, it wouldn’t in general have high utility.
x is just an input string. So, for example, each x could be a frame coming from a video camera. AIXI then has a reward function r(x), and it maximizes the sum of r(x) over some large number of time steps. In our example, let’s say that if the camera is looking at a happy puppy, r is big, if it’s looking at something else, r is small.
In the lab, AIXI might have to choose between two options (action can be handled by some separate output string, as in Hutter’s paper): 1) Don’t follow the puppy around. 2) Follow the puppy around.
Clearly, it will do 2, because r is bigger when it’s looking at a happy puppy, and 2 increases the chance of doing so. One might even say one has a puppy-following robot.
In the real world, there are more options—if you give AIXI access to a printer and some scotch tape, options look like this: 1) Don’t follow the puppy around. 2) Follow the puppy around. 3) Print out a picture of a happy puppy and tape it to the camera.
Clearly, it will do 3, because r is bigger when it’s looking at a happy puppy, and 3 increases the chance of doing so. One might even say one has a happy-puppy-looking-at maximizing robot. This time it’s even true.
The argument breaks down because you are equivocating on what the space is to search over and what the utility function in question is.
Under a given utility function U, “change the utility function to U’ ” won’t generally have positive utility. Self-awareness and pleasure-seeking aren’t some natural properties of optimization processes. They have to be explicitly built in.
Suppose you set a theorem-prover to work looking for a proof of some theorem. It’s searching over the space of proofs. There’s no entry corresponding to “pick a different and easier theorem to prove”, or “stop proving theorems and instead be happy.”
The utility function is r(x) (the “r” is for “reward function”). I’m talking about changing x, and leaving r unchanged.
Yes, I just changed the notation to be more standard. The point remains. There need not be any “x” that corresponds to “pick a new r” or to “pretend x was really x’”. If there was such an x, it wouldn’t in general have high utility.
x is just an input string. So, for example, each x could be a frame coming from a video camera. AIXI then has a reward function r(x), and it maximizes the sum of r(x) over some large number of time steps. In our example, let’s say that if the camera is looking at a happy puppy, r is big, if it’s looking at something else, r is small.
In the lab, AIXI might have to choose between two options (action can be handled by some separate output string, as in Hutter’s paper):
1) Don’t follow the puppy around.
2) Follow the puppy around.
Clearly, it will do 2, because r is bigger when it’s looking at a happy puppy, and 2 increases the chance of doing so. One might even say one has a puppy-following robot.
In the real world, there are more options—if you give AIXI access to a printer and some scotch tape, options look like this:
1) Don’t follow the puppy around.
2) Follow the puppy around.
3) Print out a picture of a happy puppy and tape it to the camera.
Clearly, it will do 3, because r is bigger when it’s looking at a happy puppy, and 3 increases the chance of doing so. One might even say one has a happy-puppy-looking-at maximizing robot. This time it’s even true.