Some thinking on what to think about is very important, unfortunately it is also very hard to get it right. For example here we can discuss optimal decisions involving probability, entirely forgetting the limited runtime and the effect of introducing risk on the efficacy of bounded calculations in the future. When you take risks, for example, you double the size of the expected-utility-calculating tree, meaning that in limited time you cut down on depth.
Then there’s this: you can think how to optimize your behaviour by single digit percentage, for example, by trying to do nonbiased estimates of your utility, which you won’t be doing very well anyway because the world is hard to predict. Or you can spend that runtime e.g. learning to program, then coming up and writing some popular application, putting it up on a relevant store, and getting way more than enough money for papering over your inefficiencies.
Some thinking on what to think about is very important, unfortunately it is also very hard to get it right. For example here we can discuss optimal decisions involving probability, entirely forgetting the limited runtime and the effect of introducing risk on the efficacy of bounded calculations in the future. When you take risks, for example, you double the size of the expected-utility-calculating tree, meaning that in limited time you cut down on depth.
Then there’s this: you can think how to optimize your behaviour by single digit percentage, for example, by trying to do nonbiased estimates of your utility, which you won’t be doing very well anyway because the world is hard to predict. Or you can spend that runtime e.g. learning to program, then coming up and writing some popular application, putting it up on a relevant store, and getting way more than enough money for papering over your inefficiencies.