# JBlack comments on Algorithmic formalization of FDT?

• Just to follow up on that third point a little more: FDT depends upon counterfactual responses, how you would have responded to inputs that you didn’t in fact observe.

If you go into a scenario where you can observe even as little as 6 bits of information, then there are 2^6 = 64 possible inputs to your decision function. FDT requires that you adopt the function with the greatest expected value over the weighted probabilities of every input, not just the one you actually observed. In the simplest possible case, each output is just one of two deterministic actions and there are only 2^(2^6) = 18446744073709551616 such functions to evaluate. If your space of possible actions is any larger than a deterministic binary action, then there will be vastly more such functions to evaluate.

Unlike both CDT and EDT, FDT is massively super-exponential in computational complexity. Pruning the space down to something that is feasibly solvable by actual computers is not something that we know how to do for any but the most ridiculously simple scenarios.

• Hmm, if FDT is so complex, how can humans evaluate it? Where does the pruning happen and how?

• Mostly they can’t, which is why there are a lot more questions posted about it than people who answer correctly. I can’t think of any FDT problem that has been answered correctly where there were more than 3 binary inputs to the decision function, and even some with 2 bits have been controversial.

For the few cases where they can, it’s the same way that humans solve any mathematical problem: via an ill defined bunch of heuristics, symmetry arguments, experience with similar problems, and some sort of intuition or insight.

• Hmm, that limits its usefulness quite a bit. For math, one can at least write an unambguous expression and use CAS like mathematica or maple and click “solve for …” Would be nice to have something like that for various DTs.