Multi-attribute utility is like playing a game where you have to pick the best toy from a bunch of toys.
Imagine you are in a toy store and your mom tells you that you can pick only one toy, but there are many toys in the store. You start to look around and see that there are different kinds of toys, such as dolls, cars, and puzzles.
You realize it's not easy to pick just one toy because some toys are too expensive, some are too big, and some are not your favorite color.
You start to think about what's important to you. You think about the cost, the size, and the color of the toy. You decide that you want a toy that is not too expensive, that is the right size for you, and that is your favorite color.
To make it easier, you assign a score to each of these things that matter to you. You give cost a score of 1-10, size a score of 1-10, and your favorite color a score of 1-10.
Then you look at each of the toys and give them a score for each of the things that matter to you.
For example, if you see a toy car that is your favorite color, but it's too big and too expensive, you might give it a score of 10 for color, but only a score of 3 for size and 2 for cost.
Then you add up all the scores for each of the toys and pick the toy with the most points.
This is what multi-attribute utility does. It helps you make a decision when there are many things to consider. You assign scores to each of the things that matter to you (attributes) and then give scores to each of the choices you have. You add up all the scores for each choice and pick the one with the most points.