CDT acts to physically cause nice things to happen. CDT can't physically cause the contents of the boxes to change, and fails to recognize the non-physical dependence of the box contents on its decision, which is a result of the logical dependence between CDT and Omega's CDT simulation. Since CDT believes its decision can't affect the contents of the boxes, it takes both in order to get any money that's there. Taking both boxes is in fact the correct course of action for the problem CDT thinks its facing, in which a guy may have randomly decided to leave some money around for them. CDT doesn't think that it will always get the $1 million; it is capable of representing a background probability that Omega did or didn't do something. It just can't factor out a part of that uncertainty, the part that's the same as its uncertainty about what it will do, into a causal relation link that points from the present to the past (or from a timeless platonic computation node to both the present and the CDT sim in the past, as TDT does).
Or from a different light, people who talked about causal decision theories historically were pretty vague, but basically said that causality was that thing by which you can influence the future but not the past or events outside your light cone, so when we build more formal versions of CDT, we make sure that's how it reasons and we keep that sense of the word causality.
Omniscient Omega doesn't entail backwards causality, it only entails omniscience. If Omega can extrapolate how you would choose boxes from complete information about your present, you're not going to fool it no matter how many times you play the game.
Imagine a machine that sorts red balls from green balls. If you put in a red ball, it spits it out Terminal A, and if you put in a green ball it spits it out Terminal B. If you showed a completely colorblind person how you could predict in which terminal a ball would get spit out of before putting it into the machine, it might look to them like backwards causality, but only forwards causality is involved.
If you know that Omega can predict your actions, you should condition your decisions on the knowledge that Omega will have predicted you correctly.
Humans are predictable enough in real life to make this sort of reasoning salient. For instance, I have a friend who, when I ask her questions such as "you know what happened to me?" or "You know what I think is pretty cool?" or any similarly open ended question, will answer "Monkeys?" as a complete non sequitur, more often than not (it's functionally her way ...
This is a simple question that is in need of a simple answer.
Because $1,000 is greater than $0, $1,001,000 is greater than $1,000,000 and those are the kind of comparisons that CDT cares about.
Please don't link to pages and pages of theorycrafting. Thank you.
You haven't seemed to respond to the 'simple' thus far and have instead defied it aggressively. That leaves you either reading the theory or staying confused.
If you ask a mathematician to find 0x + 1 for x = 3, they will answer 1. If you then ask the mathematician to find the 10th root of the factorial of the eighth Mersenne prime, multiplied by zero, plus one, they will answer 1. You may protest they didn't actually calculate the eighth Mersenne prime, find its factorial, or calculate the tenth root of that, but you can't deny they gave the right answer.
If you put CDT in a room with a million dollars in Box A and a thousand dollars in Box B (no Omega, just the boxes), and give it the choice of either A or bo...
Newcomb's problem has sequential steps - that's the key difference between it and problems like Prisoner's Dilemma. By the time the decision-agent is faced with the problem, the first step (where Omega examines you and decides how to seed the box) is already done. Absent time travel, nothing the agent does now will affect the contents of the boxes.
Consider the idea of the hostage exchange - the inherent leverage is in favor of the person who receives what they want first. It takes fairly sophisticated analysis to decide that what happened before should aff...
CDT calculates it this way: At the point of decision, either the million-dollar box has a million or it doesn't, and your decision now can't change that. Therefore, if you two-box, you always come out ahead by $1,000 over one-boxing.
I am not sure what you mean by "substitute Newcomb with a problem that consists of little more than simple calculation of priors and payoffs". If you mean that the decision algorithm should chose the the option correlated with the highest payoffs, then that's Evidential Decision Theory, and it fails on other problems- eg the Smoking Lesion.
Here is my take on the whole thing, fwiw.
The issue is assigning probability to the outcome (Omega predicted player one-boxing whereas player two-boxed), as it is the only one where two-boxing wins. Obviously any decision theorists who assigns a non-zero probability to this outcome hasn't read the problem statement carefully enough, specifically the part that says that Omega is a perfect predictor.
EDT calculates the expected utility by adding, for all outcomes (probability of outcome given specific action)*payoff of the outcome. In the Newcomb case the con...
It seems like if you haven't understood what's going on in a problem until very recently, when people explained it to you, and then you've come up with an answer to the problem that most people familiar with the subject material are objecting to.
How high is the prior for your hypothesis, that your posterior is still high after so much evidence pointing the other way?
What, exactly, is your goal in this conservation? What could an explanation why CDT two-boxes look like in order to make you accept that explanation?
You don't need to perfectly simulate Omega to play Newcomb. I am not Omega, but I bet that if I had lots of money and decided to entertain my friends with a game of Newcomb's boxes, I would be able to predict their actions with better than 50.1% accuracy.
Clearly CDT (assuming for the sake of the argument that I'm friends with CDT) doesn't care about my prediction skills, and two-boxes anyway, earning a guaranteed $1000 and a 49.9% chance of a million, for a total of $500K in expectation.
On the other hand, if one of my friends one-boxes, then he gets a 50.1% chance of a million, for a total of $501K in expectation.
Not quite as dramatic a difference, but it's there.
Because academic decision theorists say that CDT two boxes. A real causal decision theorist would, of course, one box. But the causal decision theorists in academic decision theorists' heads two box, and when people talk about causal decision theory, they're generally talking about the version of causal decision theory that is in academics' heads. This needn't make any logical sense.
You seem to be fighting the hypothetical, but I don't know if you're doing it out of mistrust or because some background would be helpful. I'll assume helpful background would be helpful... :-)
A program could be designed to (1) search for relevant sensory data within a larger context, (2) derive a mixed strategy given the input data, (3) gets more bits of salt from local thermal fluctuations than log2(number of possible actions), (4) drop the salt into a pseudo-random number generator over its derived mixed strategy, and (5) output whatever falls out as its action. This rough algorithm seems strongly deterministic in some ways, and yet also strongly reminiscent of "choice" in others.
This formulation reduces the "magic" of Omega to predicting the relatively fixed elements of the agent (ie, steps 1, 2, and 4) which seems roughly plausible as a matter of psychology and input knowledge and so on, and also either (A) knowing from this that the strategy that will be derived isn't actually mixed so the salt is irrelevant, or else (B) having access/control of the salt in step 3.
In AI design, steps 1 and 2 are under the programmer's control to some degree. Some ways of writing the program might make the AI more or less tractable/benevolent/functional/wise and it seems like it would be good to know which ways are likely to produce better outcomes before any such AI is built and achieves takeoff rather than after. Hence the interest in this thought experiment as an extreme test case. The question is not whether step 3 is pragmatically possible for an imaginary Omega to hack in real life. The question is how to design steps 1 and 2 in toy scenarios where the program's ability to decide how to pre-commit and self-edit are the central task, so that harder scenarios can be attacked as "similar to a simpler solved problem".
If you say "Your only choices are flipping a coin or saying a predetermined answer" you're dodging the real question. You can be dragged back to the question by simply positing "Omega predicts the coin flip, what then?" If there's time and room for lots and lots of words (rather than just seven words) then another way to bring attention back to the question is to explain about fighting the hypothetical, try to build rapport, see if you can learn to play along so that you can help advance a useful intellectual project.
If you still "don't get it", then please, at least don't clog up the channel. If you do get it, please offer better criticism. Like, if you know of a different but better thought experiment where effectively-optimizing self-modifying pre-commitment is the central feature of study, that would be useful.
I have read lots of LW posts on this topic, and everyone seems to take this for granted without giving a proper explanation. So if anyone could explain this to me, I would appreciate that.
This is a simple question that is in need of a simple answer. Please don't link to pages and pages of theorycrafting. Thank you.
Edit: Since posting this, I have come to the conclusion that CDT doesn't actually play Newcomb. Here's a disagreement with that statement:
And here's my response:
Edit 2: Clarification regarding backwards causality, which seems to confuse people:
Edit 3: Further clarification on the possible problems that could be considered Newcomb:
Edit 4: Excerpt from Nozick's "Newcomb's Problem and Two Principles of Choice":