In our current implementations of UDT, the agent won’t find any proof that one-boxing leads to the predictor predicting one-boxing, because the agent doesn’t “know” that it’s only going to use a small fraction of its computing resources while searching for the proof. Maybe a different implementation could fix that.
It’s not an implementation of UDT in the sense that it doesn’t talk about all possible programs and universal prior on them. If you consider UDT as generalizing to ADT, where probability assumptions are dropped, then sure.
Um, I don’t consider the universal prior to be part of UDT proper. UDT can run on top of any prior, e.g. when you use it to solve toy problems as Wei did, you use small specialized priors.
In our current implementations of UDT, the agent won’t find any proof that one-boxing leads to the predictor predicting one-boxing, because the agent doesn’t “know” that it’s only going to use a small fraction of its computing resources while searching for the proof. Maybe a different implementation could fix that.
It’s not an implementation of UDT in the sense that it doesn’t talk about all possible programs and universal prior on them. If you consider UDT as generalizing to ADT, where probability assumptions are dropped, then sure.
Um, I don’t consider the universal prior to be part of UDT proper. UDT can run on top of any prior, e.g. when you use it to solve toy problems as Wei did, you use small specialized priors.
There are no priors used in those toy problems, just one utility definition of interest.
Well, the use of any priors over possible worlds is the thing I find objectionable.