Re; Jeffrey’s decision theory, it’s not multi-agent, which is a huge limitation. Otherwise I’d agree with you.
Re: game theory, you’re right that it’s been around for a while, but it’s more “tried and false” than “tried and true”. Basically, people in geopolitics (both the study, and the activity) know by now that Nash equilibria and even correlated equilibria are not good models of how powerful entities interact, and psychologists know they’re not good models of how individuals interact. (In fact, as early as 1967, Aumann, Harsanyi, Stearns, and others all warned that mathematical models of games were a poor fit for real-world applications, e.g., in their report to government, “Models of Gradual Reduction of Arms”.) I believe a contributor to the disconnect between game theory and reality is that real-world states and even individual humans are somewhat translucent to each other, while game theoretic agents aren’t. See Halpern & Pass (2018) Game Theory for Translucent Players for a solid attempt at fixing this.
Re: causal inference, it’s true that Pearl’s causal graph framing on the topic is relatively new (the late 80′s / early 90s), as are some of his theorems (e.g., the v-structure theorem of the 90s), but much of this work just codifies and organizes practices that date back to the 1930s, with structural equation models. This isn’t to disparage the value of organizing that stuff, since it paves the way for further theoretical advancement, and it’s big part of what earned Pearl the Turing prize, which I think was very well deserved.
Regarding game theory: The examples you give are about game theory not describing actual behavior very well. But I assume we want here to use game theory as a theory of (multi-agent instrumental) rationality. So in our case it has to describe how people should interact, not necessarily how they do interact. Right?
Of course, if people do presumably interact rationality in certain cases, while game theory describes something else, then it is both normatively and descriptively inadequate. I’m not sure whether your examples are such cases. But there others. For example, both game theory and decision theory seem to recommend not to go voting in a democracy. In the former case because it seems to be a prisoner’s dilemma, in the latter because the expected utility of voting is very low. Voting being irrational seems highly counterintuitive, especially if you haven’t already been “brain washed” with those theories. They seem to miss some sort of Kantian “but if everyone did not vote” reasoning. That seems to me somewhat more excusable for decision theory, since it is not multi-agentic in the first place. But game t ’heory does indeed also seem more “tried and false” to me. Though some would bite the bullet and say voting is in fact irrational.
Re; Jeffrey’s decision theory, it’s not multi-agent, which is a huge limitation. Otherwise I’d agree with you.
Re: game theory, you’re right that it’s been around for a while, but it’s more “tried and false” than “tried and true”. Basically, people in geopolitics (both the study, and the activity) know by now that Nash equilibria and even correlated equilibria are not good models of how powerful entities interact, and psychologists know they’re not good models of how individuals interact. (In fact, as early as 1967, Aumann, Harsanyi, Stearns, and others all warned that mathematical models of games were a poor fit for real-world applications, e.g., in their report to government, “Models of Gradual Reduction of Arms”.) I believe a contributor to the disconnect between game theory and reality is that real-world states and even individual humans are somewhat translucent to each other, while game theoretic agents aren’t. See Halpern & Pass (2018) Game Theory for Translucent Players for a solid attempt at fixing this.
Re: causal inference, it’s true that Pearl’s causal graph framing on the topic is relatively new (the late 80′s / early 90s), as are some of his theorems (e.g., the v-structure theorem of the 90s), but much of this work just codifies and organizes practices that date back to the 1930s, with structural equation models. This isn’t to disparage the value of organizing that stuff, since it paves the way for further theoretical advancement, and it’s big part of what earned Pearl the Turing prize, which I think was very well deserved.
Regarding game theory: The examples you give are about game theory not describing actual behavior very well. But I assume we want here to use game theory as a theory of (multi-agent instrumental) rationality. So in our case it has to describe how people should interact, not necessarily how they do interact. Right?
Of course, if people do presumably interact rationality in certain cases, while game theory describes something else, then it is both normatively and descriptively inadequate. I’m not sure whether your examples are such cases. But there others. For example, both game theory and decision theory seem to recommend not to go voting in a democracy. In the former case because it seems to be a prisoner’s dilemma, in the latter because the expected utility of voting is very low. Voting being irrational seems highly counterintuitive, especially if you haven’t already been “brain washed” with those theories. They seem to miss some sort of Kantian “but if everyone did not vote” reasoning. That seems to me somewhat more excusable for decision theory, since it is not multi-agentic in the first place. But game t ’heory does indeed also seem more “tried and false” to me. Though some would bite the bullet and say voting is in fact irrational.