hierarchical-estimates-visualizer/packages/webpage-refactor

About

This repository creates a react webpage that allows to extract a utility function from possibly inconsistent binary comparisons.

It presents the users with a series of elements to compare, using merge-sort in the background to cleverly minimize the number of choices needed.

Then, it cleverly aggregates them, on the one hand by producing a graphical representation:

and on the other hand doing some fast and clever mean aggregation ¹:

Initially, users could only input numbers, e.g., "A is 3 times better than B". But now, users can also input distributions, using the squiggle syntax, e.g., "A is 1 to 10 times better than B", or "A is mm(normal(1, 10), uniform(0,100)) better than B".

If you want to use the utility function extractor for a project, we are happy to add a page for your project, like utility-function-extractor.quantifieduncertainty.org/your-project.

Built with

• Nextjs
• Netlify
• React
• Squiggle
• [Utility tools](to do: add links)

Usage

Navigate to utility-function-extractor.quantifieduncertainty.org/, and start comparing objects.

You can change the list of objects to be compared by clicking on "advanced options".

After comparing objects for a while, you will get a table and a graph with results. You can also use the [utility tools](to do: add link) package to process these results, for which you will need the json of comparisons, which can be found in "Advanced options" -> "Load comparisons"

Notes

The core structure is json array of objects. Only the "name" attribute is required. If there is a "url", it is displayed nicely.

[
    {
        "name": "Peter Parker",
        "someOptionalKey": "...",
        "anotherMoreOptionalKey": "...",
    },
    {
        "name": "Spiderman",
        "someOptionalKey": "...",
        "anotherMoreOptionalKey": "..."
    }
]

The core structure for links is as follows:

[
    {
        "source": "Peter Parker",
        "target": "Spiderman",
        "squiggleString": "1 to 100",
        "distance": 26.639800977355474
    },
    {
        "source": "Spiderman",
        "target": "Doctor Octopus",
        "squiggleString": "20 to 2000",
        "distance": 6.76997149080232
    },

]

A previous version of this webpage had a more complicated structure, but it has since been simplified.

Contributions and help

We welcome PR requests.

License

Distributed under the MIT License. See LICENSE.txt for more information.

To do

• Extract merge, findPath and aggregatePath functionality into different repos
• Send to mongo upon completion
• Push to github
• Push to netlify
• Don't allow further comparisons after completion
• Paths table
  • Add paths table
  • warn that the paths table is approximate.
  • However, I really don't feel like re-adding this after having worked out the distribution rather than the mean aggregation
  • However, I think it does make it more user to other users.
• Add functionality like names, etc.
  • I also don't feel like doing this
• Look back at Amazon thing which has been running
• Change README.

Footnotes

---

1. The program takes each element as a reference point in turn, and computing the possible distances from that reference point to all other points, and taking the geometric mean of these distances. This produces a number representing the value of each element, such that the ratios between elements represent the user's preferences: a utility function. However, this isn't perfect; the principled approach woud be to aggregate the distributions rather than their means. But this principled approach is much more slowly. For the principled approach, see the utility-tools repository. ↩︎