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\title{Reality Vector: A 10-Dimensional Environmental State Model for Autonomous Systems}
\author{Jeremy Blaine Thompson Beebe\\ \textit{Bxthre3 Inc. --- bxthre3inc@gmail.com --- ORCID: 0009-0009-2394-9714}}
\date{April 2026}
\begin{document}
\maketitle
\begin{abstract}\noindent
An autonomous system operating in a physical environment must reason about spatial position, temporal state, subsurface conditions, above-canopy conditions, certainty, compliance state, economic value, and historical trajectory. Existing systems model 3 to 5 axes. The Reality Vector models all 10 orthogonal dimensions simultaneously as $V_R = \{S_X, S_Y, T, Z(-), Z(+), C, L, V_f, E, G\}$. Each dimension is binary: the action is fully governed only when all 10 axes are simultaneously satisfied. The 10D vector enables the Agentic platform to reason about center-pivot irrigation with full environmental context --- below-surface compaction, above-canopy microclimate, regulatory compliance, and economic cost simultaneously.
\end{abstract}
\medskip\noindent\textbf{Keywords:} reality vector, 10-dimensional state model, environmental reasoning, autonomous systems, spatial-temporal modeling, BX3 Framework, Irrig8
\newpage
\section{The 10 Orthogonal Axes}
\begin{enumerate}
\item $S_X$: Horizontal longitude --- spatial position on Earth's surface
\item $S_Y$: Horizontal latitude --- complementary spatial coordinate
\item $T$: Timestamp index --- temporal position in operational window
\item $Z(-)$: Subsurface depth --- soil conditions from -100cm to 0
\item $Z(+)$: Above-ground height --- canopy and microclimate from 0 to +10m
\item $C$: Certainty and quality metric --- confidence in sensor readings
\item $L$: Decision state (9-Plane DAP plane index) --- regulatory compliance posture
\item $V_f$: Resolution scaling factor --- the data resolution at which observations were made
\item $E$: Economic value and cost function --- resource cost of the action
\item $G$: Compliance and governance status --- regulatory authorization state
\end{enumerate}
\section{Binary Compliance}
An action is fully governed only when all 10 axes are simultaneously satisfied: compliant or non-compliant on each axis. There is no partial credit, no continuous score to optimize. This closes the Governance Hole problem where systems maximize a compliance metric while missing critical axes like spatial hierarchy or temporal boundedness.
\section{Irrig8 Application}
The 10D Reality Vector drives every irrigation decision. A pivot zone at $S_X, S_Y$ has a $Z(-)$ profile showing compaction at 12 inches. The $Z(+)$ reading shows canopy temperature 8 degrees above ambient. $C$ is 0.94 (high confidence from redundant sensors). $L$ shows P9 Sandbox Gate approved the proposed action. $E$ shows water cost at \$0.003 per gallon against projected yield value of \$0.008 per gallon. $G$ shows water-right allocation active and within permitted volumes. Only when all 10 axes are satisfied does the valve open.
\section{Conclusion}
The Reality Vector provides the first complete, orthogonal, deterministic state model for autonomous systems operating in complex physical environments. Every decision is traceable to a specific 10D coordinate in environmental state space.
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