Interaction of this simulated TDT and you is so complicated I don’t think many of commenters here actually did the math to see how should they expect the simulated TDT agent to react in these situations. I know I didn’t. I tried, and failed.
The functions tdt() and you() accept the source code of a function as an argument, and try to maximize its return value. The implementation of tdt() could be any of our formalizations that enumerate proofs successively, which all return 1 if given the source code to tdt_utility. The implementation of you() could be simply “return 2”.
Thanks for this. I hadn’t seen someone pseudocode this out before. This helps illustrate that interesting problems lie in the scope above (callers to tdt_uility() etc) and below (implementation of tdt() etc).
I wonder if there is a rationality exercise in ‘write pseudocode for problem descriptions, explore the callers and implementations’.
Interaction of this simulated TDT and you is so complicated I don’t think many of commenters here actually did the math to see how should they expect the simulated TDT agent to react in these situations. I know I didn’t. I tried, and failed.
Maybe I’m missing something, but the formalization looks easy enough to me...
The functions tdt() and you() accept the source code of a function as an argument, and try to maximize its return value. The implementation of tdt() could be any of our formalizations that enumerate proofs successively, which all return 1 if given the source code to tdt_utility. The implementation of you() could be simply “return 2”.
Thanks for this. I hadn’t seen someone pseudocode this out before. This helps illustrate that interesting problems lie in the scope above (callers to tdt_uility() etc) and below (implementation of tdt() etc).
I wonder if there is a rationality exercise in ‘write pseudocode for problem descriptions, explore the callers and implementations’.