Algorithms to Live By: The Computer Science of Human Decisions

First, from Hill Climbing: even if you’re in the habit of sometimes acting on bad ideas, you should always act on good ones. Second, from the Metropolis Algorithm: your likelihood of following a bad idea should be inversely proportional to how bad an idea it is. Third, from Simulated Annealing: you should front-load randomness, rapidly cooling out

James thus viewed randomness as the heart of creativity.

The river meanders because it can’t think. —RICHARD KENNEY

There is no such thing as absolute certainty, but there is assurance sufficient for the purposes of human life. —JOHN STUART MILL

There is a deep message in the fact that on certain problems, randomized approaches can outperform even the best deterministic ones. Sometimes the best solution to a problem is to turn to chance rather than trying to fully reason out an answer.

There are many ways to relax a problem, and we’ve seen three of the most important. The first, Constraint Relaxation, simply removes some constraints altogether and makes progress on a looser form of the problem before coming back to reality. The second, Continuous Relaxation, turns discrete or binary choices into continua: when deciding between ic

What would you do if all jobs paid the same? The idea behind such thought exercises is exactly that of Constraint Relaxation:

The perfect is the enemy of the good. —VOLTAIRE

A Sharpie makes it impossible to drill down that deep. You can only draw shapes, lines, and boxes. That’s good. The big picture is all you should be worrying about in the beginning.