Talk:White paper on Quasi Artifactual Intelligence

Updating Quasi Axiomatic Theory to 2023 Standards

Author: Don@groupKOS.com

Copyright © 2023 Don@groupKOS.com, All rights reserved under appropriate open-source licenses

Introduction

The Quasi Axiomatic Theory was developed as a big-data tool to significant events in the live-edge of the expanding world-corpus.

Abstract and Theoretical Framework

The QAT is based on a simultaneity of relational events in dual channels of measurement. The simultaneity is registered not at a process thread in an algorithmic moment, but as registered as simultaneous within the entire set of dual measurements.

Implementation Philosophy

In this paradigm of measurement and category-frequency stratification, the data is a recording and remains immutable. A binary tree implementation for node access had no need to balance an immutable log. A delete function for a tree node isn't needed. In the category theory implementation, the data may be sparsely sampled with the same results.

The Quasi Axiomatic Theory (QAT) and its Components

The QAT facilitates the display of cross-channel relationships through two key components: Category Abstraction (cA) and Event Chemistry (eC).

Category Abstraction (cA)

Once interesting groups of categories within the data-stream are isolated by category abstraction mapping, groupings of interest are selected from the clusters on the cA mapping.

Event Chemistry (eC)

Isolation of small groups allows event chemistry abstraction to sleuth the chemistry of categorical interactions as an interactive classical graph of circles connected with lines.

The Role and Evolution of QAT

The QAT in the 911 Response Era

With contributions nationally, during the 911 response era, aiding in the global cause were the data structures of the QAT visual abstraction, navigable with event chemistry, providing access back to the source-moment of any categorical trend, and as such was the purpose of domestic surveillance.

The Creation of Ontological Access

In this notational paradigm of measurement and category frequency trending, the data is a recording and remains immutable. A binary tree implementation for data access has no need to balance an immutable log. A delete function for a tree node isn't needed.

Visual Abstraction of Relationships

Two measurement channels provide one QAT dimension of analysis providing visual abstraction of relationships in the cross-comparison. This occurs by randomly scattering onto a visual map the set of points representing all existing pairs within dual channels of measurement in the data ontology widget. The gather process accesses the proportionality map to animate the category-mapping- wherein this is a visual abstraction of dynamic relationships translated to a stratification of motions within the category-scatter-map.

Applications and Future Directions of QAT

Existing and Potential Applications

The outcome of the paradigm rendered to notation is a binary-tree/linked-list data widget where all members of a category value are linked as a chain, as category-member-chains attached to each binary tree node.

Conclusion

The binary-tree nodes each have a chain of equivalent values indexed in natural order as a linked list. The fully structured data widget affords any data by relational-path-access, including lower_category, higher_category, next_member, previous_member, with all index values anywhere within the structure also indicating relative age by natural order.

Future Work

With structured historical data access of a measured channel, a second structure is referenced holding a second channel of measurements. These two structures provide the prismatic affordance of the proportionality map of their implicit relational dynamics across a sampling of events within a time line.