Yes, austerity does have an interesting relationship with counterfactuals, which I personally consider a feature, not a bug. A strong version of austerity would rule out certain kinds of counterfactuals, particularly those that require considering events the agent is certain won’t happen. This is because austerity requires us to only include events in our model that the agent considers genuinely possible.
However, this doesn’t mean we can’t in many cases make sense of apparently counterfactual reasoning. Often when we say things like “you should have done B instead of A” or “if I had chosen differently, I would have been richer”, we’re really making forward-looking claims about similar future situations rather than genuine counterfactuals about what could have happened.
For example, imagine a sequence of similar decision problems (similar as in, you view what you learn as one decision problem as informative about the others, in a straightforward way) where you must choose between rooms A and B (then A’ and B’, etc.), where one contains $100 and the other $0. After entering a room, you learn what was in both rooms before moving to the next choice. When we say “I made the wrong choice—I should have entered room B!” (for example, after learning that you chose the room with less money), from an austerity perspective we might reconstruct the useful part of this reasoning as not really making a claim about what could have happened. Instead, we’re learning about the expected value of similar choices for future decisions, and considering the counterfactual is just an intuitive heuristic for doing that. If what was in room A is indicative of what will be in A’, then this apparent counterfactual reasoning is actually forward-looking learning that informs future choices. Now of course not all uses of counterfactuals can get this kind of reconstruction, but at least many of them that seem useful can.
It’s also worth noting that while austerity constrains counterfactuals, the JB framework can still accommodate causal decision theory approaches (like Joyce’s or Bradley’s versions) that many find attractive, and so in a sense allows certain kinds of decision-theoretic counterfactuals. Now, I think one could push back on austerity grounds even here, and I do think that some versions of CDT implemented in JB would run afoul of certain strong interpretations of austerity. However, I’d say that even with these additions, JB remains more austere than Savage’s framework, which forces agents to rank clearly impossible acts.
The core insight is that we can capture much of the useful work done by counterfactual reasoning without violating austerity by reinterpreting apparently counterfactual claims as forward-looking learning opportunities.
I’m more worried about counterfactual mugging and transparent Newcomb. Am I right that you are saying “in first iteration of transparent Newcomb austere decision theory gets no more than 1000$ but then learns that if it modifies its decision theory into more UDT-like it will get more money in similar situations”, turning it into something like son-of-CDT?
I think austerity has a weird relationship with counterfactuals?
Yes, austerity does have an interesting relationship with counterfactuals, which I personally consider a feature, not a bug. A strong version of austerity would rule out certain kinds of counterfactuals, particularly those that require considering events the agent is certain won’t happen. This is because austerity requires us to only include events in our model that the agent considers genuinely possible.
However, this doesn’t mean we can’t in many cases make sense of apparently counterfactual reasoning. Often when we say things like “you should have done B instead of A” or “if I had chosen differently, I would have been richer”, we’re really making forward-looking claims about similar future situations rather than genuine counterfactuals about what could have happened.
For example, imagine a sequence of similar decision problems (similar as in, you view what you learn as one decision problem as informative about the others, in a straightforward way) where you must choose between rooms A and B (then A’ and B’, etc.), where one contains $100 and the other $0. After entering a room, you learn what was in both rooms before moving to the next choice. When we say “I made the wrong choice—I should have entered room B!” (for example, after learning that you chose the room with less money), from an austerity perspective we might reconstruct the useful part of this reasoning as not really making a claim about what could have happened. Instead, we’re learning about the expected value of similar choices for future decisions, and considering the counterfactual is just an intuitive heuristic for doing that. If what was in room A is indicative of what will be in A’, then this apparent counterfactual reasoning is actually forward-looking learning that informs future choices. Now of course not all uses of counterfactuals can get this kind of reconstruction, but at least many of them that seem useful can.
It’s also worth noting that while austerity constrains counterfactuals, the JB framework can still accommodate causal decision theory approaches (like Joyce’s or Bradley’s versions) that many find attractive, and so in a sense allows certain kinds of decision-theoretic counterfactuals. Now, I think one could push back on austerity grounds even here, and I do think that some versions of CDT implemented in JB would run afoul of certain strong interpretations of austerity. However, I’d say that even with these additions, JB remains more austere than Savage’s framework, which forces agents to rank clearly impossible acts.
The core insight is that we can capture much of the useful work done by counterfactual reasoning without violating austerity by reinterpreting apparently counterfactual claims as forward-looking learning opportunities.
I’m more worried about counterfactual mugging and transparent Newcomb. Am I right that you are saying “in first iteration of transparent Newcomb austere decision theory gets no more than 1000$ but then learns that if it modifies its decision theory into more UDT-like it will get more money in similar situations”, turning it into something like son-of-CDT?