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PyETR

Welcome to the PyETR documentation!

PyETR (we like to pronounce it like "Peter") is a Python implementation of the Erotetic Theory of Reasoning (ETR) as presented in the book Reason & Inquiry, OUP 2023.

From the publisher:

 

Reason and Inquiry: The Erotetic Theory presents a unified theory of the human capacity for reasoning and decision-making. The erotetic theory accounts for a diverse range of empirically documented fallacies and framing effects. It shows how the same mental processes that yield fallacies can yield what logicians call first-order validity and probabilistic coherence in reasoning, as well as rational decision-making as conceived by economists.

The book's central idea is that our minds naturally aim at resolving issues, and if we are sufficiently inquisitive in the process, we can avoid mistakes. The erotetic theory holds that both the successes and the failures of reason are due to this aim. Rationality is secured if we reach what is described by the theory as erotetic equilibrium.

Note for readers of Reason and Inquiry

Anywhere you see a box like this one will be a reference to the book Reason & Inquiry.

For very short discussion of the erotetic theory see Koralus and Wang-Maścianica 2023. The earliest version of a fragment of the erotetic theory of reason (not fully equivalent to the present version) goes back to Koralus and Mascarenhas 2013.

Most users can dive straight in here for the overview of the book and code. This documentation focuses features of the python package and does not attempt to provide a standalone motivation or explanation of the erotetic theory, which is a book length endeavour. Book readers who may wish to understand how it relates to the code should instead begin here, before returning to the overview in "Getting Started"."

The documentation is structured as follows.

  • Getting started contains instructions for Installation and running Python.

  • Usage explains in detail how to get started with the package, how to construct views, and provides examples.

  • Advanced Usage looks "under the hood" and at some more advanced view construction.

  • Theory recaps the ideas from Reason & Inquiry that are important for PyETR. Users who are also readers of the book should also read this for some important information.

  • Reference shows the available cases, operations and inference methods.

  • Glossary describes terms used throughout the documentation.

  • For Developers provides a summary of how to work on the package and produce new versions.

  • Credits lists the people that worked on this project.

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Top tip! If you're wondering what a term or operation means, or how it works, remember to use the search bar at the top - this often will show you to the right section!