Because I suspect that there are only so many functionally different types of connections between events (at the very least, I see no hint that there must be infinitely many) and once you’ve found them all you will have the possibility of writing a DT that can’t be led to corner itself into suboptimal outcomes due to blind spots.
at the very least, I see no hint that there must be infinite ones
Am I correct in interpreting this as “infinitely many of them”? If so, I am curious as to what you mean by “functionally different types of connections between events”. Could you provide an example of some “types of connections between events”? Functionally different ones to be sure.
Presumably, the relevance must be your belief that decision theories differ in just how many of these different kinds of connections they handle correctly. Could you illustrate this by pointing out how the decision theory of your choice handles some types of connections, and why you have confidence that it does so correctly?
Am I correct in interpreting this as “infinitely many of them”?
Oops, yes. Fixed.
If so, I am curious as to what you mean by “functionally different types of connections between events”. Could you provide an example of some “types of connections between events”? Functionally different ones to be sure.
CDT can ‘see’ the classical, everyday causal connections that are marked in formulas with the symbol “>” (and I’d have to spend several hours reading at least the Stanford Encyclopaedia before I could give you a confident definition of that), but it cannot ‘see’ the connection in Newcomb’s problem between the agent’s choice of boxes and the content of the opaque box (sometimes called ‘retrocausality’).
Presumably, the relevance must be your belief that decision theories differ in just how many of these different kinds of connections they handle correctly. Could you illustrate this by pointing out how the decision theory of your choice handles some types of connections, and why you have confidence that it does so correctly?
I don’t have a favourite formal decision theory, because I am not sufficiently familiar with the underlying math and with the literature of discriminating scenarios to pick a horse. If you’re talking about the human decision “theory” of mine I described above, it doesn’t explicitly do that; the key hand-waving passage is “figure out which actions are most efficient at leading to the best worlds”, meaning I’ll use whatever knowledge I currently possess to estimate how big is the set of Everett branches where I do X and get A, compared to the set of those where I do X and get B. (For example, six months ago I hadn’t heard of the concept of acausal connections and didn’t account for them at all while plotting the likelihoods of possible futures, whereas now I do—at least technically; in practice, I think that between human agents they are a negligible factor. For another example, suppose that some years from now I became convinced that the complexity of human minds, and the variability between different ones, were much greater than I previously thought; then, given the formulation of Newcomb’s problem where Omega isn’t explicitly defined as a perfect simulator and all we know is that it has had a 100% success rate so far, I would suitably increase my estimation of the chances of Omega screwing up and making two-boxing profitable.)
CDT can ‘see’ the classical, everyday causal connections that are marked in formulas with the symbol “>” (and I’d have to spend several hours reading at least the Stanford Encyclopaedia before I could give you a confident definition of that), but it cannot ‘see’ the connection in Newcomb’s problem between the agent’s choice of boxes and the content of the opaque box (sometimes called ‘retrocausality’).
Ok, so if I understand you, there are only some finite number of valid kinds of connections between events and when we have all of them incorporated—when our decision theory can “see” each of them—we are then all done. We have the final, perfect decision theory (FPDT).
But what do you do then when someone—call him Yuri Geller—comes along and points out that we left out one important kind of connection: the “superspooky” connection. And then he provides some very impressive statistical evidence that this connection exists and sets up games in front of large (paying) audiences in which FPDT agents fail to WIN. He then proclaims the need for SSPDT.
Or, if you don’t buy that, maybe you will prefer this one. Yuri Geller doesn’t really exist. He is a thought experiment. Still the existence of even the possibility of superspooky connections proves that they really do exist and hence that we need to have SADT—Saint Anselm’s Decision Theory.
Ok, I’ve allowed my sarcasm to get the better of me. But the question remains—how are you ever going to know that you have covered all possible kinds of connections between events?
But the question remains—how are you ever going to know that you have covered all possible kinds of connections between events?
You can’t, I guess. Within an established mathematical model, it may be possible to prove that a list of possible configurations of event pairs {A, B} is exhaustive. But the model may always prove in need of expansion or refinement—whether because some element gets understood and modellised at a deeper level (eg the nature of ‘free’ will) or, more worryingly, because of paradigm shifts about physical reality (eg turns out we can time travel).
Because I suspect that there are only so many functionally different types of connections between events (at the very least, I see no hint that there must be infinitely many) and once you’ve found them all you will have the possibility of writing a DT that can’t be led to corner itself into suboptimal outcomes due to blind spots.
Am I correct in interpreting this as “infinitely many of them”? If so, I am curious as to what you mean by “functionally different types of connections between events”. Could you provide an example of some “types of connections between events”? Functionally different ones to be sure.
Presumably, the relevance must be your belief that decision theories differ in just how many of these different kinds of connections they handle correctly. Could you illustrate this by pointing out how the decision theory of your choice handles some types of connections, and why you have confidence that it does so correctly?
Oops, yes. Fixed.
CDT can ‘see’ the classical, everyday causal connections that are marked in formulas with the symbol “>” (and I’d have to spend several hours reading at least the Stanford Encyclopaedia before I could give you a confident definition of that), but it cannot ‘see’ the connection in Newcomb’s problem between the agent’s choice of boxes and the content of the opaque box (sometimes called ‘retrocausality’).
I don’t have a favourite formal decision theory, because I am not sufficiently familiar with the underlying math and with the literature of discriminating scenarios to pick a horse. If you’re talking about the human decision “theory” of mine I described above, it doesn’t explicitly do that; the key hand-waving passage is “figure out which actions are most efficient at leading to the best worlds”, meaning I’ll use whatever knowledge I currently possess to estimate how big is the set of Everett branches where I do X and get A, compared to the set of those where I do X and get B. (For example, six months ago I hadn’t heard of the concept of acausal connections and didn’t account for them at all while plotting the likelihoods of possible futures, whereas now I do—at least technically; in practice, I think that between human agents they are a negligible factor. For another example, suppose that some years from now I became convinced that the complexity of human minds, and the variability between different ones, were much greater than I previously thought; then, given the formulation of Newcomb’s problem where Omega isn’t explicitly defined as a perfect simulator and all we know is that it has had a 100% success rate so far, I would suitably increase my estimation of the chances of Omega screwing up and making two-boxing profitable.)
Ok, so if I understand you, there are only some finite number of valid kinds of connections between events and when we have all of them incorporated—when our decision theory can “see” each of them—we are then all done. We have the final, perfect decision theory (FPDT).
But what do you do then when someone—call him Yuri Geller—comes along and points out that we left out one important kind of connection: the “superspooky” connection. And then he provides some very impressive statistical evidence that this connection exists and sets up games in front of large (paying) audiences in which FPDT agents fail to WIN. He then proclaims the need for SSPDT.
Or, if you don’t buy that, maybe you will prefer this one. Yuri Geller doesn’t really exist. He is a thought experiment. Still the existence of even the possibility of superspooky connections proves that they really do exist and hence that we need to have SADT—Saint Anselm’s Decision Theory.
Ok, I’ve allowed my sarcasm to get the better of me. But the question remains—how are you ever going to know that you have covered all possible kinds of connections between events?
You can’t, I guess. Within an established mathematical model, it may be possible to prove that a list of possible configurations of event pairs {A, B} is exhaustive. But the model may always prove in need of expansion or refinement—whether because some element gets understood and modellised at a deeper level (eg the nature of ‘free’ will) or, more worryingly, because of paradigm shifts about physical reality (eg turns out we can time travel).