Algorithms to Live By: The Computer Science of Human Decisions
Brian Christian, Tom Griffiths
amazon.com
Algorithms to Live By: The Computer Science of Human Decisions
Brian Christian, Tom Griffiths
amazon.comAnd the challenge has only increased with the development of the printing press, the nightly news, and social media—innovations that allow our species to spread language mechanically.
What would you do if you weren’t afraid?
Having instincts tuned by evolution for a world in constant flux isn’t necessarily helpful in an era of industrial standardization.
we search with our quick eyes and sort with slow hands.
As a species, being constrained by the past makes us less perfectly adjusted to the present we know but helps keep us robust for the future we don’t.
(In a wedding seating optimization, for instance, we might relax the constraint that tables each hold ten people max, allowing overfull tables but with some kind of elbow-room penalty.) When an optimization problem’s constraints say “Do it, or else!,” Lagrangian Relaxation replies, “Or else what?” Once we can color outside the lines—even just a lit
... See moreJames thus viewed randomness as the heart of creativity.
every prediction, crucially, involves thinking about two distinct things: what you know and what you don’t. That is, it’s an attempt to formulate a theory that will account for the experiences you’ve had to date and say something about the future ones you’re guessing at.
In fact, for any possible drawing of w winning tickets in n attempts, the expectation is simply the number of wins plus one, divided by the number of attempts plus two: (w+1)⁄(n+2).