If the other players can see what action you’ll take, then they may simply exploit you.
Isn’t this a variant of the “agent simulates predictor” problem (with you playing the role of the predictor)? Thus any agent capable of exploiting you has to prove to you that it won’t, in order to get anything from you. That’s kind of what happens with your Nicerbots; even if perfectly predictable, they’re not really exploitable in any strong sense (they won’t cooperate with a defector).
I think the point I was making here was a bit less clear than I wanted it to be. I was saying that, if you use predictable exploration on actions rather than policies, then you only get to see what happens when you predictably take a certain action. This is good for learning pure equilibria in games, but doesn’t give information which would help the agent reach the right mixed equilibria when randomized actions should be preferred; and indeed, it doesn’t seem like such an agent would reach the right mixed equilibria.
I believe the “predictable exploration on policies” approach solves agent-simulates-predictor just fine, along with other problems (including counterfactual mugging) which require “some degree of updatelessness” without requiring the full reflective stability which we want from updatelessness.
Isn’t this a variant of the “agent simulates predictor” problem (with you playing the role of the predictor)? Thus any agent capable of exploiting you has to prove to you that it won’t, in order to get anything from you. That’s kind of what happens with your Nicerbots; even if perfectly predictable, they’re not really exploitable in any strong sense (they won’t cooperate with a defector).
I think the point I was making here was a bit less clear than I wanted it to be. I was saying that, if you use predictable exploration on actions rather than policies, then you only get to see what happens when you predictably take a certain action. This is good for learning pure equilibria in games, but doesn’t give information which would help the agent reach the right mixed equilibria when randomized actions should be preferred; and indeed, it doesn’t seem like such an agent would reach the right mixed equilibria.
I believe the “predictable exploration on policies” approach solves agent-simulates-predictor just fine, along with other problems (including counterfactual mugging) which require “some degree of updatelessness” without requiring the full reflective stability which we want from updatelessness.