I have sympathy with both one-boxers and two-boxers in Newcomb's problem. Contrary to this, however, many people on Less Wrong seem to be staunch and confident one-boxers. So I'm turning to you guys to ask for help figuring out whether I should be a staunch one-boxer too. Below is an imaginary dialogue setting out my understanding of the arguments normally advanced on LW for one-boxing and I was hoping to get help filling in the details and extending this argument so that I (and anyone else who is uncertain about the issue) can develop an understanding of the strongest arguments for one-boxing.
The two-boxer is trying to maximise money (utility). They are interested in the additional question of which bits of that money (utility) can be attributed to which things (decisions/agent types). "Caused gain" is a view about how we should attribute the gaining of money (utility) to different things.
So they agree that the problem is about maximising money (utility) and not "caused gain". But they are interested in not just which agents end up with the most money (utility) but also which aspects of those agents is responsible for them receiving the money. Specifically, they are interested in whether the decisions the agent makes are responsible for the money they receive. This does not mean they are trying to maximise something other than money (utility). It means they are interested in maximising money and then also in how you can maximise money via different mechanisms.
An additional point (discussed intelligence.org/files/TDT.pdf) is that CDT seems to recommend modifying oneself to a non-CDT based decision theory. (For instance, imagine that the CDTer contemplates for a moment the mere possibility of encountering NPs and can cheaply self-modify). After modification, the interest in whether decisions are responsible causally for utility will have been eliminated. So this interest seems extremely brittle. Agents able to modify and informed of the NP scenario will immediately lose the interest. (If the NP seems implausible... (read more)