Is this decision framework that uses information, time, and space, sound?

Introduction:

The Triangular Decision Cycle Framework Diagram is a visual tool used to track the flow of data within decision cycles. It was originally developed as a theoretical framework. The TDCF builds upon the Decision Cycle Framework (DCF) by providing a visual diagram that tracks the flow of data in decision cycles. The DCF is based on the DTM, a framework that classifies data sources into three types: spatial, time-series, and information/hypothesis, and allows for nine possible combinations of these sources to be used in decision cycles.

Data Sources (DS):

Rational Agents deal with different types of data sources: observations/actions in space (S), series of observations/actions over time (T), and information/hypothesis available to an observer (I). AIXI is an example of a rational agent. Spatial data, time series data, and information can all be represented as sequences, which can potentially match each other.

Data Transfer Methods (DTM):

The data sources can be combined in nine different ways designated as "Input→Output (Name)" . For example:
S→S (Duplicate) – Photographing an object
S→T (Playback) – Playing a song from sheet music
T→S (Record) – Recording a song onto a record
T→T (Repeat) – Repeating an experiment
I→T (Explain) – Explaining a theory verbally
I→S (Depict) – Depicting a theory in a graph or writing it down
T→I (Build, Agile) – Building a project based on a theory heard in a meeting
S→I (Build, Waterfall) – Building a project based on a theory read in a document
I→I (Model) – Modeling a hypothesis, such as weather simulation.

Each data transfer method has an associated ratio that measures the size of the input relative to the size of the output. These ratios are necessary for measuring different objects that perform DTMs. For example:
S→S (Duplicate): (input meters/output meters); scale – dimensionless
T→T (Repeat): (input seconds/output seconds); speedup – dimensionless
I→I (Model): (input bits/output bits); lossy compression – dimensionless
T→S (Record), S→T (Playback): (input meters/output seconds); velocity and inverse
T→I (Build, Agile), I→T (Explain): (input bits/output seconds); bandwidth and inverse
I→S (Depict), S→I (Build, Waterfall): (input bits/output meters); data density and inverse

Decision Cycle Framework (DCF):

The framework outlines a decision-making cycle that includes the following stages:
Data Collection: Duplicating (S→S) or recording (T→S) data.
Hypothesis Generation: Creating a theory based on the data, generating possible depictions (I→S) – AIXI brute forces this. A literature review can be included that listens or reads about prior theories (T→I) and (S→I).
Testing, Simulation, and Planning: Testing, simulating, and planning based on the hypothesis by creating a model (I→I) then recording data (T→S) (data recorded from the simulation).
Communication: (optional) Verbally explaining the hypothesis to others (I→T).
Implementation: Playing back the simulation (S→T).
Iteration: Repeating the entire cycle as needed by repeating the experiment (T→T).

Triangular Decision Cycle Framework (TDCF):

The TDCF is a graphical representation of the DCF that helps to visualize the stages of the decision cycle and their interconnections.
Assign {S, T, I} to the vertices of an equilateral triangle. For each DTM, let its coordinate be Input + Output. Now connect the DTMs at each stage, and connect the stages using arrows. There is now a triangle that visually depicts a decision cycle as a loop. This creates an equilateral triangle with the dimensionless DTMs at the vertices and the dimensional DTMs in between.