Well too bad for all the theories that can’t handle slight randomness, because in our universe you can’t implement an agent which does not have slight uncorrelated randomness to it’s output; that’s just how our universe is.
I don’t understand your comment. Our proof-theoretic algorithms can handle worlds with randomness just fine, because the logical fact of the algorithm’s return value will be more or less correlated with many physical facts. The proof-theoretic algorithms don’t require slight randomness to work, and my grandparent comment gave a reason why it seems hard to write a version that relies completely on slight randomness to kill spurious proofs, as you suggested. Of course if you do find a way, it will be cool.
Well, your grandparent’s comment spoke of a problem with adding randomness, rather than with lack of necessity to add randomness. Maybe i simply misunderstood it.
Note btw that the self description will have to include randomness, to be an accurate description of an imperfect agent.
Let me try to explain. Assume you have an agent that’s very similar to our proof-theoretic ones, but also has a small chance of returning a random action. Moreover, the agent’s self-description includes a mention of the random variable V that makes the agent return a random action.
The first problem is that statements like “A()==a” are no longer logical statements. That seems easy to fix by making the agent look at conditional expected values instead of logical implications.
The second and more serious problem is this: how many independent copies of V does the world contain? Imagine the agent is faced with Newcomb’s Problem. If the world program contains only one copy of V that’s referenced by both instances of the agent, that amounts to abusing the problem formulation to tell the agent “your copies are located here and here”. And if the two copies of the agent use uncorrelated instances of V, then looking at conditional expected values based on V buys you nothing. Figuring out the best action reduces to same logical question that the proof-theoretic algorithms are faced with.
Well too bad for all the theories that can’t handle slight randomness, because in our universe you can’t implement an agent which does not have slight uncorrelated randomness to it’s output; that’s just how our universe is.
I don’t understand your comment. Our proof-theoretic algorithms can handle worlds with randomness just fine, because the logical fact of the algorithm’s return value will be more or less correlated with many physical facts. The proof-theoretic algorithms don’t require slight randomness to work, and my grandparent comment gave a reason why it seems hard to write a version that relies completely on slight randomness to kill spurious proofs, as you suggested. Of course if you do find a way, it will be cool.
Well, your grandparent’s comment spoke of a problem with adding randomness, rather than with lack of necessity to add randomness. Maybe i simply misunderstood it.
Note btw that the self description will have to include randomness, to be an accurate description of an imperfect agent.
Let me try to explain. Assume you have an agent that’s very similar to our proof-theoretic ones, but also has a small chance of returning a random action. Moreover, the agent’s self-description includes a mention of the random variable V that makes the agent return a random action.
The first problem is that statements like “A()==a” are no longer logical statements. That seems easy to fix by making the agent look at conditional expected values instead of logical implications.
The second and more serious problem is this: how many independent copies of V does the world contain? Imagine the agent is faced with Newcomb’s Problem. If the world program contains only one copy of V that’s referenced by both instances of the agent, that amounts to abusing the problem formulation to tell the agent “your copies are located here and here”. And if the two copies of the agent use uncorrelated instances of V, then looking at conditional expected values based on V buys you nothing. Figuring out the best action reduces to same logical question that the proof-theoretic algorithms are faced with.