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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Logical Line-Of-Sight Makes Games Sequential or Loopy, published by StrivingForLegibility on January 19, 2024 on LessWrong.
In the last post, we talked about strategic time and the strategic time loops studied in open-source game theory. In that context, agents have logical line-of-sight to each other and the situation they're both facing, which creates a two-way information flow at the time each is making their decision. In this post I'll describe how agents in one context can use this logical line-of-sight to condition their behavior on how they behave in other contexts. This in turn makes those contexts strategically sequential or loopy, in a way that a purely causal decision theory doesn't pick up on.
Sequential Games and Leverage
As an intuition pump, consider the following ordinary game: Alice and Bob are going to play a Prisoners' Dilemma, and then an Ultimatum game. My favorite framing of the Prisoners' Dilemma is by Nicky Case: each player stands in front of a machine which accepts a certain amount of money, e.g. $100.[1] Both players choose simultaneously whether to put some of their own money into the machine. If Alice places $100 into the machine in front of her, $200 comes out of Bob's machine, and vice versa.
If a player withholds their money, nothing comes out of the other player's machine. We call these strategies Cooperate and Defect respectively.
Since neither player can cause money to come out of their own machine, Causal Decision Theory (CDT) identifies Defect as a dominant strategy for both players. Dissatisfaction with this answer has motivated many to dig into the foundations of decision theory, and coming up with different conditions that enable Cooperation in the Prisoners' Dilemma has become a cottage industry for the field.
I myself keep calling it the Prisoners' Dilemma (rather than the Prisoner's Dilemma) because I want to frame it as a dilemma they're facing together, where they can collaboratively implement mechanisms that incentivize mutual Cooperation. The mechanism I want to describe today is leverage: having something the other player wants, and giving it to them if and only if they do what you want.
Suppose that the subsequent Ultimatum game is about how to split $1,000. After the Prisoners' Dilemma, a fair coin is flipped to determine Alice and Bob's roles in the Ultimatum game. The evaluator can employ probabilistic rejection to shape the incentives of the proposer, so that the proposer has the unique best-response of offering a fair split. (According to the evaluator's notion of fairness.) And both players might have common knowledge that "a fair split" depends on what both players did in the Prisoners' Dilemma.
If Alice is the evaluator, and she Cooperated in the first round but Bob Defected, then she is $200 worse-off than if Bob had Cooperated, and she can demand that Bob compensate her for this loss. Similarly, if Alice is the proposer, she might offer Bob $500 if he Cooperated but $300 if he Defected. Since Bob only gained $100 compared to Cooperating, his best-response is to Cooperate if he believes Alice will follow this policy. And Bob can employ the same policy, stabilizing the socially optimal payoff of ($600, $600) as a Nash equilibrium where neither has an incentive to change their policy.
Crucially, this enforcement mechanism relies on each player having enough leverage in the subsequent game to incentivize Cooperation in the first round. If the Ultimatum game had been for stakes less than $200, this would be less than a Defector can obtain for themselves if the other player Cooperates. Knowing that neither can incentivize Cooperation, both players might fall back into mutual Defection.
Bets vs Unexploitability
Even if Alice knows she has enough leverage that she can incentivize Bob to Cooperate, she might be uncert...
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