I have yet to see a description of TDT which allows me to calculate what TDT does on an arbitrary problem. But I do know that I have seen long lists from Eliezer of problems that TDT does not solve that he thinks it ought to be improved so as to solve.
The world isn’t sufficiently formalized for us to meet that standard for any decision theory (though we come closer with CDT and TDT than with EDT, in my opinion). However, cousin_it has a few recent posts on formalized situations where an agent of a more TDT (actually, UDT) type does strictly better than a CDT one in the same situation. I don’t know of any formalization (or any fuzzy real-world situation) where the opposite is true.
I apparently misled you by using that word “arbitrary”. I’m not asking for solutions to soft problems that are difficult to formalize. Simply solutions to the standard kinds of games already formalized in game theory. For example, the game of Chicken). Can anyone point me to a description that tells me what play TDT would make in this game? Or what mixed strategy it would use? Both assuming and not assuming the reading of each other’s code.
ETA: Slightly more interesting than the payoff matrix shown in the wikipedia article is the case when the payoff for a win is 2 units, with a loss still costing only −1. This means that in the iterated version, the negotiated solution would be to alternate wins. But we are interested in the one-shot case.
Can TDT find a correlated equilibrium? If not, which Nash equilibrium does it pick? Or does it always chicken out? Where can I learn this information?
But I do know that I have seen long lists from Eliezer of problems that TDT does not solve that he thinks it ought to be improved so as to solve.
Since CDT and EDT don’t solve those problems either, all this justifies saying is that TDT does better on some problems, and the same on others, not “worse on others”.
A “nemesis” environment that feeds misleading evidence to a decision theory’s underlying epistimology does not indicate the sort of problem illustrated by an environment in which a decision theory does something stupid with true information.
What you asked for was a case where a decision theory did worse than its rivals.
However, that seems pretty trivial if it behaves differently from them—you just consider an appropriate pathological environment set up to punish that decision theory.
Do you have an example of a problem on which CDT or EDT does better than TDT?
I have yet to see a description of TDT which allows me to calculate what TDT does on an arbitrary problem. But I do know that I have seen long lists from Eliezer of problems that TDT does not solve that he thinks it ought to be improved so as to solve.
The world isn’t sufficiently formalized for us to meet that standard for any decision theory (though we come closer with CDT and TDT than with EDT, in my opinion). However, cousin_it has a few recent posts on formalized situations where an agent of a more TDT (actually, UDT) type does strictly better than a CDT one in the same situation. I don’t know of any formalization (or any fuzzy real-world situation) where the opposite is true.
I apparently misled you by using that word “arbitrary”. I’m not asking for solutions to soft problems that are difficult to formalize. Simply solutions to the standard kinds of games already formalized in game theory. For example, the game of Chicken). Can anyone point me to a description that tells me what play TDT would make in this game? Or what mixed strategy it would use? Both assuming and not assuming the reading of each other’s code.
ETA: Slightly more interesting than the payoff matrix shown in the wikipedia article is the case when the payoff for a win is 2 units, with a loss still costing only −1. This means that in the iterated version, the negotiated solution would be to alternate wins. But we are interested in the one-shot case.
Can TDT find a correlated equilibrium? If not, which Nash equilibrium does it pick? Or does it always chicken out? Where can I learn this information?
Since CDT and EDT don’t solve those problems either, all this justifies saying is that TDT does better on some problems, and the same on others, not “worse on others”.
For every possible decision theory, there is a “nemesis” environment—where it does extremely badly. That is no-free-lunch fall out.
A “nemesis” environment that feeds misleading evidence to a decision theory’s underlying epistimology does not indicate the sort of problem illustrated by an environment in which a decision theory does something stupid with true information.
What you asked for was a case where a decision theory did worse than its rivals.
However, that seems pretty trivial if it behaves differently from them—you just consider an appropriate pathological environment set up to punish that decision theory.
Yes, in the context of Perplexed dismissing examples of TDT doing better than CDT because CDT was being stupid with true information.