Algorithms to Live By Brian Christian, Tom Griffiths
Enhancing our understanding of decision-making skills and learning how computer algorithms work.
Instead of thinking about only the next decision you will make, think about all of the decisions you are going to make about the same options in the future.
Explore vs Exploit
When should you be exploring new options and when should you start settling for the best option you already know? Consider these concepts:
Regret Minimisation Framework: When you look back on your life when you’re 80, what will you regret least?
Exploring and Ageing
Exploring: In decision making, we consider the single highest pay-off on our single decision, but in the long term, it’s way more efficient to first explore your options, before exploiting the highest pay-off decision.
Ageing: Deepest insight about later life is that you can exploit knowledge acquired over decades — life should get better over time.
Sorting
Sorting is one of the most fundamental problems that computers solve for us.
Bubble sort + Insertion sort: when you put the book alphabetically against a shelf of books, there are a billion different permutations and options.
Mergesort: when you compare two sets against each other and sort each time, then compare them against the next set
Bucketsort: putting things into buckets/classifying
Single elimination: all it tells you is the 1st place, but all other places in the ranking are not truly representative
Round robin: gives you full information, but also requires the most effort.
Optimal Stopping
When you are hiring, scouting houses to buy, and options to consider — when should you stop looking?
You stop looking too early, and you don’t know if someone better isn’t going to come along. You stop too late, you might have passed on the best candidate already.
The Math Approach To Stopping
Mathematically — you should stop looking after evaluating 37% of all the options you’re willing to look at. After the 37% option — if anything/anyone comes along who is better than everyone else before you should make the decision.