Are ya winning, son?
Hello, I've been reading through various Newcomblike Problems, in order to get a better understanding of the differences between each Decision Theory. From what I can tell, it seems like each Decision Theory gets evaluated based on whether they are able to "win" in each of these thought experiments. Thus, there is an overarching assumption that each thought experiment has an objectively "right" and "wrong" answer, and the challenge of Decision Theory is to generate algorithms that will guarantee that the agent will choose the "right" answer. However, I am having some trouble in seeing how some of these problems have an objectively "winning" state. In Newcomb's Problem, obviously one can say that one-boxing "wins" because you get way more money than two-boxing, and these are the only two options available. Of course, even here there is some room for ambiguity, as said by Robert Nozick: > To almost everyone it is perfectly clear and obvious what should be done. The difficulty is that these people seem to divide almost evenly on the problem, with large numbers thinking that the opposing half is just being silly. But other Newcomblike Problems leave me with some questions. Take, for example, the Smoking Lesion Problem. I am told that smoking is the winning decision here (as long as we take a suspension of disbelief from the fact that smoking is bad in the real world). But I'm not sure why that makes such a big difference. Yes, the problem states we would prefer to smoke if we could, but our preferences can come from many different dimensions such as our understanding of the environment, not just a spontaneous inner desire. So when EDT says that you shouldn't smoke because it increase the probability of having a cancerous lesion, then one could say that that information has shaped your preference. To use a different analogy, I may desire ice cream because it tastes good, but I may still prefer not to eat it out of my understanding of how it impacts my health and weig
I didn't mean it to be so simplistic. I am just considering that if there is a known limitation of AI, no matter how powerful it is, that could be used as the basis of a system an AI could not circumvent. For example, if there was a shutdown system where the only way to disable it would require solving the halting problem.