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Sorry for the length. In a few paragraphs there's a reader's guide so you can skip around. I have tried to put the most valuable stuff up first. Consider only reading the introduction. Starting from every moment, there are choices you could make. Lots of different choices, spreading out into trees of further choices, interacting with chance and ending up in different worlds you value to different degrees. As you think about which path to take, you learn more about what is likely on each branch. But as you gain more knowledge, you lose some opportunities: branches get left behind as you follow the track of waiting and thinking. How are we supposed to figure out how to explore this space effectively? We need solutions that trade off integrating knowledge of the tree, future options and the cost of spending time thinking. These are hard questions, and we don't have complete answers, but we might look to those who have studied similar problems. One field of study that has overlap with this conundrum is that of algorithms. We can look at algorithms as case studies in rationality. Making decisions is hard, and computer science is partly the study of finding the best decision given time and space constraints -- and humans certainly face those constraints. We also face forgetfulness, impulsivity, weak mental maths ... But we at least face time and space constraints. Algorithms to Live By by Brian Christian & Tom Griffiths is an exploration of the applicability of algorithms from computer science to human decision problems. Though the book is flawed, I have changed my behaviour in some ways because of it, and am considering changing others as well. Here are the three changes I've made that have been most worthwhile so far: * When I first get a set of new options that is likely to stay stable into the future, I prioritise choosing a new option over repeating a good choice (from Explore / Exploit). Odds of around 2:1 / 66% confident that this is an improvement. * I s