Alfred Harwood

This post was written during the agent foundations fellowship with Alex Altair funded by the LTFF. Thanks to Alex, Jose, Daniel, Cole, and Einar for reading and commenting on a draft. The Good Regulator Theorem, as published by Conant and Ashby in their 1970 paper (cited over 1700 times!) claims to show that 'every good regulator of a system must be a model of that system', though it is a subject of debate as to whether this is actually what the paper shows. It is a fairly simple mathematical result which is worth knowing about for people who care about agent foundations and selection theorems. You might have heard about the Good Regulator Theorem in the context of John Wentworth's 'Gooder Regulator' theorem and his other improvements on the result. Unfortunately, the original 1970 paper is notoriously unfriendly to readers. It makes misleading claims, doesn't clearly state what exactly it shows and uses strange non-standard notation and cybernetics jargon ('coenetic variables' anyone?). If you want to understand the theorem without reading the paper, there are a few options. John Wentworth's post has a nice high-level summary but refers to the original paper for the proof. John Baez's blogpost is quite good but is very much written in the spirit of trying to work out what the paper is saying, rather than explaining it intuitively. I couldn't find an explanation in any control theory textbooks (admittedly my search was not exhaustive). A five year-old stackexchange question, asking for a rigorous proof, goes unanswered. The best explainer I could find was Daniel L. Scholten's 'A Primer for Conant and Ashby's Good-Regulator Theorem' from the mysterious, now-defunct 'GoodRegulatorProject.org' (link to archived website). This primer is nice, but really verbose (44 pages!). It is also aimed at approximately high-school (?) level, spending the first 15 pages explaining the concept of 'mappings' and conditional probability. Partly to test my understanding of the theore