algorithms to live by by brian christian

In both 20, seven of the Top 10 films were either sequels or prequels. The number of movie sequels has steadily increased over the last decade. Hollywood is a prime example of the exploit tactic. Given 15 opportunities to choose which slot machine would win, 47% used Win-Stay, Lose-Shift strategies, and 22% chose machines randomly instead of staying with a machine that paid out. Then switch to another machine this method was proven to be more reliable than chance.Ī psychology study found that given choices, people often 'over explore' rather than exploit a win. Choose a machine at random and play it until you lose. People are more likely to visit their favorite restaurant on their last night in town than risk something new.ĭeveloped in 1952 by mathematician Herbert Robins, the 'Win-Stay, Lose-Shift' algorithm uses slot machines as a metaphor. The payoff of this algorithm depends entirely on how much time you have to make decisions. The 'explore/exploit' trade-off refers to the need to balance the tried and tested with the new and risky. Someone allots 37% of their time to research before they make a decision, then commits to the very next 'best choice' they find. The '37% rule' refers to a series of steps, or algorithms, that someone must follow to make the best decision within a set amount of time. In Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths, programmer and researcher Brian Christian and psychology and cognitive science professor at UC Berkeley Tom Griffiths share the many ways that algorithms shape everything from the way we remember things to how we make big and small decisions. Algorithms are everywhere, from following a recipe to the order in which you sort your email.

Can computer science teach us the secrets of life? Perhaps not, but it can shed light on how certain everyday processes work and how to exploit them.

Algorithms to live by by brian christian