112 lines
4.4 KiB
Markdown
112 lines
4.4 KiB
Markdown
## About
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This repository creates a react webpage that allows to extract a utility function from possibly inconsistent binary comparisons.
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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.
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<p align="center">
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<img width="50%" height="50%" src="./public/example-prompt.png">
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</p>
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Then, it cleverly aggregates them, on the one hand by producing a graphical representation:
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<p align="center">
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<img width="50%" height="50%" src="./public/example-graph.png">
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</p>
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and on the other hand doing some fast and clever mean aggregation [^1]:
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<p align="center">
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<img width="50%" height="50%" src="./public/example-table.png">
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</p>
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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](https://www.squiggle-language.com/) 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".
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**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`**.
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## Built with
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- [Nextjs](https://nextjs.org/)
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- [Netlify](https://github.com/netlify/netlify-plugin-nextjs/#readme)
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- [React](https://reactjs.org/)
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- [Squiggle](https://www.squiggle-language.com/)
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- [Utility tools](https://github.com/quantified-uncertainty/utility-function-extractor/tree/master/packages/utility-tools)
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## Usage
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Navigate to [utility-function-extractor.quantifieduncertainty.org/](https://utility-function-extractor.quantifieduncertainty.org/), and start comparing objects.
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You can change the list of objects to be compared by clicking on "advanced options".
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After comparing objects for a while, you will get a table and a graph with results. You can also use the [utility tools](https://github.com/quantified-uncertainty/utility-function-extractor/tree/master/packages/utility-tools) package to process these results, for which you will need the json of comparisons, which can be found in "Advanced options" -> "Load comparisons"
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## Notes
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The core structure is json array of objects. Only the "name" attribute is required. If there is a "url", it is displayed nicely.
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```
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[
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{
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"name": "Peter Parker",
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"someOptionalKey": "...",
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"anotherMoreOptionalKey": "...",
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},
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{
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"name": "Spiderman",
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"someOptionalKey": "...",
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"anotherMoreOptionalKey": "..."
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}
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]
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```
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The core structure for links is as follows:
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```
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[
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{
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"source": "Peter Parker",
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"target": "Spiderman",
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"squiggleString": "1 to 100",
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"distance": 26.639800977355474
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},
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{
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"source": "Spiderman",
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"target": "Jonah Jameson",
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"squiggleString": "20 to 2000",
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"distance": 6.76997149080232
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},
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]
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```
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A previous version of this webpage had a more complicated structure, but it has since been simplified.
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## Contributions and help
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We welcome PR requests.
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## License
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Distributed under the MIT License. See LICENSE.txt for more information.
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## To do
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- [x] Extract merge, findPath and aggregatePath functionality into different repos
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- [x] Send to mongo upon completion
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- [x] Push to github
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- [x] Push to netlify
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- [x] Don't allow further comparisons after completion
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- [x] Paths table
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- [x] Add paths table
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- [x] warn that the paths table is approximate.
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- I really don't feel like re-adding this after having worked out the distribution rather than the mean aggregation
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- On the other hand, I think it does make it more user to other users.
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- [x] Change README.
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- [ ] Add functionality like names, etc.
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- I also don't feel like doing this
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- [ ] Look back at Amazon thing which has been running
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- [ ] Simplify Graph and DynamicSquiggleChart components
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- [ ] Add squiggle component to initial comparison?
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[^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.
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