This article is an excerpt from the Shortform book guide to "Algorithms to Live By" by Brian Christian and Tom Griffiths. Shortform has the world's best summaries and analyses of books you should be reading.

Do you know what makes you happy in life? How do you know whether a certain choice or decision will make you happy in the end?

You never know for sure whether a certain path is going to make you happy in the end. According to Brian Christian and Thomas Griffiths, the authors of Algorithms to Live By, computer science has the answer to this dilemma: to maximize happiness in your life, pursue whatever opportunity has a chance to be the greatest.

Here is why to maximize happiness, you need to put your faith in the unknown.

## Life Is a “Multi-Armed Bandit” Problem

Christian and Griffiths frame life as a complex “multi-armed bandit” problem, referring to a model computer scientists use in machine learning. The multi-armed bandit is a theoretical experiment in which one decision-making agent is presented with a row of slot machines (“one-armed bandits”) and must determine how to maximize their winnings without knowing the odds for any machine. The agent must try out different machines and learn from the outcomes to figure out which will pay off the most.

To do so, the agent strikes a balance between using the machines that have proven to pay out in the past and trying new machines to see if they pay out more—balancing “exploitation” and “exploration,” as they say in computer science.

Christian and Griffiths argue that life works in much the same way. The only way to know for certain if something will make you happy is if you try it for yourself. This could be a place to live, a relationship, or a career—life is about spending more time on the things that make you happy and less on the things that don’t.

Just like in the multi-armed bandit problem, you have to find a balance between trying new things and staying in your comfort zone. The question is: How much of each is best?

### The Algorithm and Why It Works

Christian and Griffiths describe the closest thing to an optimal solution to this problem that computer science has to offer. In 1985, some mathematicians developed a new approach to the multi-armed bandit problem with the goal of minimizing regret, that is, making it the agent’s first priority to prevent valuable missed opportunities.

Christian and Griffiths explain that the most successful algorithms at accomplishing this goal are known as “Upper Confidence Bound” algorithms. These algorithms recommend making decisions based on your options’ best-case scenarios. Pursue whatever opportunity in life has the potential to pay out the most, even if you think a jackpot is extremely unlikely, since the only way to know for sure whether or not it’ll pay off is to test it yourself. Then, if you’ve given something a shot and determined that it’s not worth your while, adjust accordingly and shoot for the moon somewhere else.

Christian and Griffiths suggest you practice this by putting greater faith in the unknown. When you know nothing about a situation—for example, if you’re set up on a blind date or offered an intriguing but unfamiliar job—act as if the best-case scenario is going to happen.

Rule #1: As your remaining opportunities decrease, experiment less.

One exception to this rule depends on the interval of time you have left to make decisions. Christian and Griffiths state that the value of new discoveries decreases as you run out of time to take advantage of them. Old favorites, on the other hand, are never going to get any worse.

As a result, Christian and Griffiths argue that you should eagerly explore the unknown until a certain point, then do nothing but revel in the favorites you’ve already discovered. If it’s the last day you have with your best friend before they move away, you’re better off spending time with them instead of meeting up with a stranger from a dating app.

Christian and Griffiths note that this correlation between experimentation and time is reflected in the stages of human life. Young children do nothing but explore and experiment. Parents and caretakers provide kids everything they need so they can be free to discover what activities and behavior are most likely to make them happy.

In contrast, elderly people typically quit experimenting altogether. They don’t usually try to meet new people, instead spending most of their time with the close friends and family that they already know will make them happy. Christian and Griffiths argue that this is why studies show that older people are more satisfied with their social lives and overall well-being than young adults. They’re reaping the rewards of a lifetime of successful experimentation.

Rule #2: Trust your past experience more than you want to.

Christian and Griffiths cite studies showing that humans tend to explore and experiment beyond what is optimal, unduly trusting what is new and neglecting to take full advantage of opportunities that have proven to be reliable in the past. For example, if the average person were trying out a new pop-up clothing shop, comparing it with the stores they already shop at, they would typically flip-flop between the two instead of figuring out which is better and sticking with it—even if the new store sells them cheaply-made clothes.

However, the authors propose that this human tendency may be more rational than the studies indicate, given the fact that we live in a constantly changing world. It’s often worth giving previously disappointing experiences a second chance in case things have gotten better. Just because one item from the clothing store fell apart after a week doesn’t mean that all of them will.

Despite this, Christian and Griffiths make the case that in today’s world, the payoffs for various options in our lives change less than ever before. Mass production and corporate standards mean that the products and services you choose to buy will be remarkably consistent. According to the authors, your instinct to over-explore is more likely to harm than help you.

Consequently, when you’re making decisions that matter, it’s worth overriding your instincts and trusting the objective records of your past experience. If you got salmonella from a food truck, it’s unlikely you’ll have a satisfying experience eating there again.

How to Maximize Happiness: Put Faith in the Unknown

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• How to schedule your to-do list like a computer
• Why making random decisions is sometimes the smartest thing to do
• Why you should reject the first 37% of positions in your job search

#### Darya Sinusoid

Darya’s love for reading started with fantasy novels (The LOTR trilogy is still her all-time-favorite). Growing up, however, she found herself transitioning to non-fiction, psychological, and self-help books. She has a degree in Psychology and a deep passion for the subject. She likes reading research-informed books that distill the workings of the human brain/mind/consciousness and thinking of ways to apply the insights to her own life. Some of her favorites include Thinking, Fast and Slow, How We Decide, and The Wisdom of the Enneagram.