Using these number, it appears that your expected gain is [p2 + 4(1-p)p + p(p+4(1-p))]/(2-p)

Do you mean "1+p" instead of "2-p" at the end there? If not, where does "2-p" come from?

Since there are N=2 individuals, the CDP thus cancels both the 2 and the (1+p) factors

Why do you say that (N=2), since the number of individuals is actually random? If you EXIT at X, then the individual at Y doesn't exist, right?

Do you think CDP can be formalized sufficiently so that it can be applied mechanically after transforming a decision problem into some formal representation (like a decision tree, or world program as in UDT1)? The way it is stated now, it seems too ambiguous to say what is the solution to a given problem under CDP.