I haven’t considered this in great detail, but if there are N variables, then I think the causal discovery runtime is O(N2). As we mention in the paper (footnote 5) there may be more efficient causal discovery algorithms that make use of certain assumptions about the system.
On adoption, perhaps if one encounters a situation where the computational cost is too high, one could coarse-grain their variables to reduce the number of variables. I don’t have results on this at the moment but I expect that the presence of agency (none, or some) is robust to the coarse-graining, though the exact number of agents is not (example 4.3), nor are the variables identified as decisions/utilities (Appendix C).
I haven’t considered this in great detail, but if there are N variables, then I think the causal discovery runtime is O(N2). As we mention in the paper (footnote 5) there may be more efficient causal discovery algorithms that make use of certain assumptions about the system.
On adoption, perhaps if one encounters a situation where the computational cost is too high, one could coarse-grain their variables to reduce the number of variables. I don’t have results on this at the moment but I expect that the presence of agency (none, or some) is robust to the coarse-graining, though the exact number of agents is not (example 4.3), nor are the variables identified as decisions/utilities (Appendix C).