If your goal is to figure out what to have for breakfast, not much relevance at all. If your goal is to program an automated decision-making system to figure out what breakfast supplies to make available to the population of the West Coast of the U.S., perhaps quite a lot. If your goal is to program an automated decision-making system to figure out how to optimize all available resources for the maximum benefit of humanity, perhaps even more.
There are lots of groups represented on LW, with different perceived needs. Some are primarily interested in self-help threads, others primarily interested in academic decision-theory threads, and many others. Easiest is to ignore threads that don’t interest you.
If your goal is to program an automated decision-making system to figure out what breakfast supplies to make available to the population of the West Coast of the U.S., perhaps quite a lot.
This example has nothing like the character of the one-box/two-box problem or the PD-with-mental-clone problem described in the article. Why should it require an “advanced” decision theory? Because people’s consumption will respond to the supplies made available? But standard game theory can handle that.
There are lots of groups represented on LW, with different perceived needs. [...]Easiest is to ignore threads that don’t interest you.
It’s not that I’m not interested; it’s that I’m puzzled as to what possible use these “advanced” decision theories can ever have to anyone.
OK, ignore those examples for a second, and ignore the word “advanced.”
The OP is drawing a distinction between CDT, which he claims fails in situations where competing agents can predict one another’s behavior to varying degrees, and other decision theories, which don’t fail. If he’s wrong in that claim, then articulating why would be helpful.
If, instead, he’s right in that claim, then I don’t see what’s useless about theories that don’t fail in that situation. At least, it certainly seems to me that competing agents predicting one another’s behavior is something that happens all the time in the real world. Does it not seem that way to you?
But the basic assumption of standard game theory, which I presume he means to include in CDT, is that the agents can predict each other’s behavior—it is assumed that each will make the best move they possibly can.
I don’t think that predicting behavior is the fundamental distinction here. Game theory is all about dealing with intelligent actors who are trying to anticipate your own choices. That’s why the Nash equilibrium is generally a probabilistic strategy—to make your move unpredictable.
But the basic assumption of standard game theory, which I presume he means to include in CDT, is that the agents can predict each other’s behavior—it is assumed that each will make the best move they possibly can.
Not quite. A unique Nash equilibrium is an un-exploitable strategy; you don’t need to predict what the other agents will do, because the worst expected utility for you is if they also pick the equilibrium. If they depart, you can often profit.
Non-unique Nash equilibria (like the coordination game) are a classical game theory problem without a general solution.
Classical game theory uses the axiom of independence to avoid having to predict other agents in detail. The point of the advanced decision theories is that we can sometimes do better than that outcome if independence is in fact violated.
If your goal is to figure out what to have for breakfast, not much relevance at all.
If your goal is to program an automated decision-making system to figure out what breakfast supplies to make available to the population of the West Coast of the U.S., perhaps quite a lot.
If your goal is to program an automated decision-making system to figure out how to optimize all available resources for the maximum benefit of humanity, perhaps even more.
There are lots of groups represented on LW, with different perceived needs. Some are primarily interested in self-help threads, others primarily interested in academic decision-theory threads, and many others. Easiest is to ignore threads that don’t interest you.
This example has nothing like the character of the one-box/two-box problem or the PD-with-mental-clone problem described in the article. Why should it require an “advanced” decision theory? Because people’s consumption will respond to the supplies made available? But standard game theory can handle that.
It’s not that I’m not interested; it’s that I’m puzzled as to what possible use these “advanced” decision theories can ever have to anyone.
OK, ignore those examples for a second, and ignore the word “advanced.”
The OP is drawing a distinction between CDT, which he claims fails in situations where competing agents can predict one another’s behavior to varying degrees, and other decision theories, which don’t fail. If he’s wrong in that claim, then articulating why would be helpful.
If, instead, he’s right in that claim, then I don’t see what’s useless about theories that don’t fail in that situation. At least, it certainly seems to me that competing agents predicting one another’s behavior is something that happens all the time in the real world. Does it not seem that way to you?
But the basic assumption of standard game theory, which I presume he means to include in CDT, is that the agents can predict each other’s behavior—it is assumed that each will make the best move they possibly can.
I don’t think that predicting behavior is the fundamental distinction here. Game theory is all about dealing with intelligent actors who are trying to anticipate your own choices. That’s why the Nash equilibrium is generally a probabilistic strategy—to make your move unpredictable.
Not quite. A unique Nash equilibrium is an un-exploitable strategy; you don’t need to predict what the other agents will do, because the worst expected utility for you is if they also pick the equilibrium. If they depart, you can often profit.
Non-unique Nash equilibria (like the coordination game) are a classical game theory problem without a general solution.
Classical game theory uses the axiom of independence to avoid having to predict other agents in detail. The point of the advanced decision theories is that we can sometimes do better than that outcome if independence is in fact violated.
I’m not sure that equating “CDT” with “standard game theory” as you reference it here is preserving the OP’s point.