I formulated a little problem. Care to solve it?
You are given the following information:
Your task is to hide a coin in your house (or any familiar finite environment).
After you've hidden the coin your memory will be erased and restored to a state just before you receiving this information.
Then you will be told about the task (i.e that you have hidden a coin), and asked to try to find the coin.
If you find it you'll lose, but you will be convinced that if you find it you win.
So now you're faced with finding an optimal strategy to minimize the probability of finding the coin within a finite time-frame.
Bear in mind that any chain of reasoning leading up to a decision of location can be generated by you while trying to find the coin.
You might come to the conclusion that there cant exist an optimal strategy other than randomizing. But if you randomize, then you have the risk of placing the coin at a location where it can be easily found, like on a table or on the floor. You could eliminate those risky locations by excluding them as alternatives in your randomization process, but that would mean including a chain of reasoning!
Here's a deterministic solution that does at least as well as hiding the coin randomly (I think?). Take the expected amount of time t it would take to find the coin by random search. Write down all the deterministic coin-hiding algorithms you can think of on a piece of paper as fast as you can, starting with the most obvious. Continue until t time units have elapsed, and then use the last algorithm you thought of.
This does assume we're counting the time it takes your future self to compute your hiding algorithm towards the time it takes him/her to find the coin.