Algorithms to Live By: The Computer Science of Human Decisions

Constraint Relaxation. In this technique, researchers remove some of the problem’s constraints and set about solving the problem they wish they had. Then, after they’ve made a certain amount of headway, they try to add the constraints back

geometric discounting of future reward,

LRU in a number of scenarios and found that LRU consistently performed the closest to clairvoyance.

your total amount of regret will probably never stop increasing, even

When we see the first applicant, we have no information—she’ll always appear to be the best yet. When we see the third applicant, we have no agency—we have to make an offer to the final applicant,

This is an algorithm known as Hill Climbing—since the search through a space of solutions, some better and some worse, is commonly thought of in terms of a landscape with hills and valleys, where your goal is to reach the highest peak.

What would you do if you weren’t afraid?

When we apply Bayes’s Rule with a normal distribution as a prior, on the other hand, we obtain a very different kind of guidance. Instead of a multiplicative rule, we get an Average Rule:

when the cache is full, to evict whichever item we’ll need again the longest from now.

Anyone who has experienced a snake bite or a lightning strike will tend to retell those singular stories for the rest of their lives. And those stories will be so salient that they will be picked up and retold by others.