Theme One Program • Motivation

[Jon Awbrey]

Theme One Program • Motivation 1
• https://inquiryintoinquiry.com/2024/06/03/theme-one-program-motivation-1-b/

All,

The main idea behind the Theme One program is the efficient use
of graph‑theoretic data structures for the tasks of “learning”
and “reasoning”.

I am thinking of “learning” in the sense of learning about an
environment, in essence, gaining information about the nature
of an environment and being able to apply the information
acquired to a specific purpose.

Under the heading of “reasoning” I am simply lumping together
all the ordinary sorts of practical activities which would
probably occur to most people under that name.

There is a natural relation between the tasks. Learning the
character of an environment leads to the recognition of laws
which govern the environment and making full use of that
recognition requires the ability to reason logically
about those laws in abstract terms.

Resources —

Theme One Program • Overview
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Overview

Theme One Program • Exposition
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Exposition

Theme One Program • User Guide
• https://www.academia.edu/5211369/Theme_One_Program_User_Guide

Survey of Theme One Program
• https://inquiryintoinquiry.com/2024/02/26/survey-of-theme-one-program-6/

Regards,

Jon

cc: https://www.academia.edu/community/LY0BKD
cc: https://mathstodon.xyz/@Inquiry/112554698776574635

[Jon Awbrey]

Theme One Program • Motivation 2
• https://inquiryintoinquiry.com/2024/06/04/theme-one-program-motivation-2-b/

All,

A side‑effect of working on the Theme One program over the
course of a decade was the measure of insight it gave me into
the reasons why empiricists and rationalists have so much trouble
understanding each other, even when those two styles of thinking
inhabit the very same soul.

The way it came about was this. The code from which the program is
currently assembled initially came from two distinct programs, ones
I developed in alternate years, at first only during the summers.

In the “Learner” program I sought to implement a Humean empiricist
style of learning algorithm for the adaptive uptake of coded sequences
of occurrences in the environment, say, as codified in a formal language.
I knew all the theorems from formal language theory telling how limited
any such strategy must ultimately be in terms of its generative capacity,
but I wanted to explore the boundaries of that capacity in concrete
computational terms.

In the “Modeler” program I aimed to implement a variant of Peirce's
graphical syntax for propositional logic, making use of graph‑theoretic
extensions I had developed over the previous decade.

As I mentioned, work on those two projects proceeded in a parallel series
of fits and starts through interwoven summers for a number of years, until
one day it dawned on me how the “Learner”, one of whose aliases was “Index”,
could be put to work helping with sundry substitution tasks the “Modeler”
needed to carry out.

So I began integrating the functions of the “Learner” and the “Modeler”,
at first still working on the two component modules in an alternating
manner, but devoting a portion of effort to amalgamating their principal
data structures, bringing them into convergence with each other, and
unifying them over a common basis.

Another round of seasons and many changes of mind and programming
style, I arrived at a unified graph‑theoretic data structure, strung
like a wire through the far‑flung pearls of my programmed wit. But the
pearls I polished in alternate years maintained their shine along axes
of polarization whose grains remained skew in regard to each other.

To put it more plainly, the strategies I imagined were the smartest tricks
to pull from the standpoint of optimizing the program’s performance on the
“Learning” task I found the next year were the dumbest moves to pull from
the standpoint of its performance on the “Reasoning” task. I gradually
came to appreciate that trade‑off as a “discovery”.

Resources —

Theme One Program • Overview
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Overview

Theme One Program • Exposition
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Exposition

Theme One Program • User Guide
• https://www.academia.edu/5211369/Theme_One_Program_User_Guide

Survey of Theme One Program
• https://inquiryintoinquiry.com/2024/02/26/survey-of-theme-one-program-6/

Regards,

Jon

cc: https://www.academia.edu/community/VodZxj
cc: https://mathstodon.xyz/@Inquiry/112554698776574635

[Jon Awbrey]

Theme One Program • Motivation 3
• https://inquiryintoinquiry.com/2024/06/05/theme-one-program-motivation-3-b/

All,

Sometime around 1970 John B. Eulenberg came from Stanford to
direct Michigan State's Artificial Language Lab, where I would
come to spend many interesting hours hanging out all through the
70s and 80s. Along with its research program the lab did a lot of
work on augmentative communication technology for limited mobility
users and the observations I made there prompted the first inklings
of my “Learner” program.

Early in that period I visited John's course in mathematical linguistics,
which featured “Laws of Form” among its readings, along with the more
standard fare of Wall, Chomsky, Jackendoff, and the Unified Science
volume by Charles Morris which credited Peirce with pioneering the
pragmatic theory of signs. I learned about Zipf's Law relating the
lengths of codes to their usage frequencies and I named the earliest
avatar of my “Learner” program “XyPh”, partly after Zipf and playing
on the xylem and phloem of its tree data structures.

Resources —

Theme One Program • Overview
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Overview

Theme One Program • Exposition
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Exposition

Theme One Program • User Guide
• https://www.academia.edu/5211369/Theme_One_Program_User_Guide

Survey of Theme One Program
• https://inquiryintoinquiry.com/2024/02/26/survey-of-theme-one-program-6/

Regards,

Jon

cc: https://www.academia.edu/community/LgrG9M
cc: https://mathstodon.xyz/@Inquiry/112554698776574635

[Jon Awbrey]

Theme One Program • Motivation 4
• https://inquiryintoinquiry.com/2024/06/06/theme-one-program-motivation-4-b/

All,

From Zipf's Law and the category of “things that vary inversely with
frequency” I got my first brush with the idea that keeping track of
usage frequencies is part and parcel of building efficient codes.

In its first application the environment the “Learner” has to learn
is the usage behavior of its user, as given by finite sequences of
characters from a finite alphabet, which sequences of characters
might as well be called “words”, together with finite sequences of
those words which might as well be called “phrases” or “sentences”.
In other words, Job One for the Learner is the job of constructing
a “user model”.

In that frame of mind we are not seeking anything so grand as a
Universal Induction Algorithm but simply looking for any approach
to give us a leg up, complexity wise, in Interactive Real Time.

Resources —

Theme One Program • Overview
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Overview

Theme One Program • Exposition
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Exposition

Theme One Program • User Guide
• https://www.academia.edu/5211369/Theme_One_Program_User_Guide

Survey of Theme One Program
• https://inquiryintoinquiry.com/2024/02/26/survey-of-theme-one-program-6/

Regards,

Jon

cc: https://www.academia.edu/community/VXJaG1
cc: https://mathstodon.xyz/@Inquiry/112554698776574635

[Jon Awbrey]

Theme One Program • Motivation 5
• https://inquiryintoinquiry.com/2024/06/07/theme-one-program-motivation-5-b/

All,

Since I'm working from decades‑old memories of first inklings
I thought I might peruse the web for current information about
Zipf's Law.

I see there is now something called the Zipf–Mandelbrot (and
sometimes –Pareto) Law and that was interesting because my wife
Susan Awbrey made use of Mandelbrot's ideas about self‑similarity
in her dissertation and communicated with him about it. So there's
more to read up on.

Just off‑hand, though, I think my “Learner” is dealing with a
different problem. It has more to do with the savings in effort a
learner gets by anticipating future experiences based on its record
of past experiences than the savings it gets by minimizing bits of
storage as far as mechanically possible. There is still a type of
compression involved but it's more like Korzybski's “time‑binding”
than space‑savings proper. Speaking of old memories …

The other difference I see is that Zipf's Law applies to an established
and preferably large corpus of linguistic material, while my Learner has
to start from scratch, accumulating experience over time, making the best
of whatever data it has at the outset and every moment thereafter.

Resources —

Theme One Program • Overview
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Overview

Theme One Program • Exposition
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Exposition

Theme One Program • User Guide
• https://www.academia.edu/5211369/Theme_One_Program_User_Guide

Survey of Theme One Program
• https://inquiryintoinquiry.com/2024/02/26/survey-of-theme-one-program-6/

Regards,

Jon

cc: https://www.academia.edu/community/5wbAEN
cc: https://mathstodon.xyz/@Inquiry/112554698776574635

[Jon Awbrey]

Theme One Program • Motivation 6
• https://inquiryintoinquiry.com/2024/06/08/theme-one-program-motivation-6-b/

All,

Comments I made in reply to a correspondent's questions about
delimiters and tokenizing in the Learner module may be worth
sharing here.

In one of the projects I submitted toward a Master's in psychology
I used the Theme One program to analyze samples of data from my
advisor's funded research study on family dynamics. In one phase
of the study observers viewed video‑taped sessions of family members
(parent and child) interacting in various modes (“play” or “work”)
and coded qualitative features of each moment's activity over
a period of time.

The following page describes the application in more detail and
reflects on its implications for the conduct of scientific inquiry
in general.

Exploratory Qualitative Analysis of Sequential Observation Data
• https://oeis.org/wiki/User:Jon_Awbrey/Exploratory_Qualitative_Analysis_of_Sequential_Observation_Data

In this application a “phrase” or “string” is a fixed‑length sequence
of qualitative features and a “clause” or “strand” is a sequence of
such phrases delimited by what the observer judges to be a significant
pause in the action.

In the qualitative research phases of the study one is simply attempting to
discern any significant or recurring patterns in the data one possibly can.

In this case the observers tokenize their observations according to
a codebook which has passed enough intercoder reliability studies
to afford a measure of confidence it captures meaningful aspects
of whatever reality is passing before their eyes and ears.

Resources —

Theme One Program • Overview
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Overview

Theme One Program • Exposition
• https://oeis.org/wiki/Theme_One_Program_%E2%80%A2_Exposition

Theme One Program • User Guide
• https://www.academia.edu/5211369/Theme_One_Program_User_Guide

Survey of Theme One Program
• https://inquiryintoinquiry.com/2024/02/26/survey-of-theme-one-program-6/

Regards,

Jon

cc: https://www.academia.edu/community/L2YMYM
cc: https://mathstodon.xyz/@Inquiry/112554698776574635