Agent Semantics, Semantic Spacetime, and Graphical Reasoning

TL;DR

This paper explores the Semantic Spacetime graph model, its formal properties, and how it supports directed knowledge and process modeling, highlighting issues like information leakage and the role of boundary states.

Contribution

It formalizes the Semantic Spacetime model with a scalable representation and clarifies the role of absorbing states and boundary information in semantic graphs.

Findings

Defined a finite γ(3,4) representation for scalable operations

Identified the role of absorbing states in information leakage

Linked boundary states to intentionality and information injection

Abstract

Some formal aspects of the Semantic Spacetime graph model are presented, with reference to its use for directed knowledge representations and process modelling. A finite $\gamma(3,4)$ representation is defined to form a closed set of operations that can scale to any degree of semantic complexity. The Semantic Spacetime postulates bring predictability with minimal constraints to pathways in graphs. The ubiquitous appearance of absorbing states in any partial graph means that a graph process leaks information. The issue is closely associated with the issue of division by zero, which signals a loss of closure and the need for manual injection of remedial information. The Semantic Spacetime model (and its Promise Theory) origins help to clarify how such absorbing states are associated with boundary information where intentionality can enter.