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\section{Operational-Premise Taxonomy (OPT)}
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Because OPT introduces several new labels, we present those here before tackling background and related work topics.

OPT classes are defined by dominant mechanism; hybrids are explicit compositions:

\begin{itemize}[leftmargin=1.6em]
\item \textbf{Learnon (\Lrn)} — Parametric learning within an individual (gradient/likelihood/return updates).
\item \textbf{Evolon (\Evo)} — Population adaptation via variation, selection, inheritance.
\item \textbf{Symbion (\Sym)} — Symbolic/logic inference over discrete structures (KB, clauses, proofs).
\item \textbf{Probion (\Prb)} — Probabilistic modeling and approximate inference (posteriors, ELBO).
\item \textbf{Scholon (\Sch)} — Deliberative search and planning (heuristics, DP, graph search).
\item \textbf{Controlon (\Ctl)} — Feedback control and state estimation in dynamical systems.
\item \textbf{Swarmon (\Swm)} — Collective/swarm coordination with local rules and emergence.
\end{itemize}

\noindent \emph{Hybrid notation.}~We use \hyb{A+B}~for co-operative mechanisms, \hyb{A/B}~for hierarchical nesting (outer/inner), \hyb{A\{B,C\}}~for parallel ensembles, and \hyb{[A→B]}~for pipelines (Appendix~\ref{app:optcode}).