What’s “complete uncertainty”? How exploitable you are depends on who tries to exploit you. The opponent is also uncertain. If the opponent is Omega, you probably should be absolutely certain, because it’ll find the single exact set of circumstances that make you lose. But if the opponent is also fallible, you can count on the outcome not being the worst-case scenario, and therefore not being able to estimate the value of that worse-case scenario is not fatal. An almost formal analogy is analysis of algorithms in worst case and average case: worst case analysis applies to the optimal opponent, average case analysis to random opponent, and in real life you should target something in between.
The “always defect” strategy is part of a Nash equilibrium. The quining cooperator is part of a Nash equilibrium. IMO that’s one of the minimum requirements that a good strategy must meet. But a strategy that cooperates whenever its “mathematical intuition module” comes up blank can’t be part of any Nash equilibrium.
“Nash equilibrium” is far from being a generally convincing argument. Mathematical intuition module doesn’t come up blank, it gives probabilities of different outcomes, given the present observational and logical uncertainty. When you have probabilities of the other player acting each way depending on how you act, the problem is pretty straightforward (assuming expected utility etc.), and “Nash equilibrium” is no longer a relevant concern. It’s when you don’t have a mathematical intuition module, don’t have probabilities of the other player’s actions conditional on your actions, when you need to invent ad-hoc game-theoretic rituals of cognition.
What’s “complete uncertainty”? How exploitable you are depends on who tries to exploit you. The opponent is also uncertain. If the opponent is Omega, you probably should be absolutely certain, because it’ll find the single exact set of circumstances that make you lose. But if the opponent is also fallible, you can count on the outcome not being the worst-case scenario, and therefore not being able to estimate the value of that worse-case scenario is not fatal. An almost formal analogy is analysis of algorithms in worst case and average case: worst case analysis applies to the optimal opponent, average case analysis to random opponent, and in real life you should target something in between.
The “always defect” strategy is part of a Nash equilibrium. The quining cooperator is part of a Nash equilibrium. IMO that’s one of the minimum requirements that a good strategy must meet. But a strategy that cooperates whenever its “mathematical intuition module” comes up blank can’t be part of any Nash equilibrium.
“Nash equilibrium” is far from being a generally convincing argument. Mathematical intuition module doesn’t come up blank, it gives probabilities of different outcomes, given the present observational and logical uncertainty. When you have probabilities of the other player acting each way depending on how you act, the problem is pretty straightforward (assuming expected utility etc.), and “Nash equilibrium” is no longer a relevant concern. It’s when you don’t have a mathematical intuition module, don’t have probabilities of the other player’s actions conditional on your actions, when you need to invent ad-hoc game-theoretic rituals of cognition.