\section{Etymological Glossary of OPT Class Names}
\label{app:opt-etymology}

The Operational Premise Taxonomy (OPT) uses short three-letter codes to denote
fundamental operative mechanisms (\Lrn, \Evo, \Sym, \Prb, \Sch, \Ctl, \Swm).
For mnemonic and conceptual coherence, each mechanism is also associated with a
semantically suggestive ``particle-style'' label in \emph{-on}, evoking both a
unit of behavior and an operative principle (by analogy with terms such as
``neuron'', ``phonon'', ``boson'', ``fermion''). This appendix summarizes the
etymological motivations for these labels.

\begin{description}

\item[\textbf{Lrn} --- \emph{Learnon}.]
  The mechanism \Lrn~covers parametric learning systems: differentiable models
  with trainable parameters (e.g., neural networks trained by gradient descent,
  linear models with least-squares updates, temporal-difference learning).
  The label \emph{Learnon} combines modern English \emph{learn} with the suffix
  \emph{-on} to denote a basic unit or agent of learning activity. The verb
  \emph{learn} traces back to Old English \emph{leornian}, ``to acquire
  knowledge, to study'', from Proto-Germanic \emph{*liznojan}. \emph{Learnon}
  thus names the operative principle ``that which learns by adjusting its
  internal parameters''.

  \item[\textbf{Evo} --- \emph{Evolon}.]
  The mechanism \Evo~comprises population-based adaptive systems: genetic
  algorithms, genetic programming, evolutionary strategies, and related methods
  grounded in variation, inheritance, and selection. The label \emph{Evolon}
  derives from Latin \emph{evolutio} (``unrolling, unfolding'') via
  \emph{evolution}, plus \emph{-on} as a unit suffix. \emph{Evolon} names ``a
  unit of evolutionary adaptation''---that is, a system whose primary
  operation is the evolutionary updating of a population of candidate
  solutions.

  \item[\textbf{Sym} --- \emph{Symon}.]
  The mechanism \Sym~denotes symbolic reasoning: rule-based expert systems,
  theorem provers, logic programming, and other forms of explicit symbolic
  manipulation. The label \emph{Symon} is rooted in Greek \emph{symbolon}
  (``token, sign'') and \emph{symballein} (``to throw together, to compare''),
  via Latin \emph{symbolum} and modern English \emph{symbol}. The \emph{-on}
  suffix again marks a unit or agent, so \emph{Symon} denotes systems whose
  defining operation is the manipulation of explicit symbols and rules.

  \item[\textbf{Prb} --- \emph{Probion}.]
  The mechanism \Prb~captures probabilistic inference: Bayesian networks,
  probabilistic graphical models, Monte Carlo methods, and related stochastic
  reasoning tools. The label \emph{Probion} derives from Latin
  \emph{probabilis} (``provable, likely'') via \emph{probability}, plus
  \emph{-on}. A \emph{Probion} system is one whose central operative premise is
  updating or querying probability distributions, rather than deterministic
  logic, parametric learning, or search over explicit alternatives.

  \item[\textbf{Sch} --- \emph{Scholon}.]
  The mechanism \Sch~covers search and related operations: heuristic search,
  combinatorial optimization, constraint satisfaction, and state-space
  exploration. The label \emph{Scholon} is based on Greek \emph{scholē}
  (``leisure devoted to learning, study'') and its descendants in Latin
  \emph{schola} and modern English \emph{school}, \emph{scholastic}. These
  terms historically refer to structured inquiry and systematic examination.
  The \emph{-on} suffix yields \emph{Scholon} as ``an agent or unit of ordered
  inquiry'', emphasizing that \Sch mechanisms operate by disciplined search
  through a space of possibilities.

  \item[\textbf{Ctl} --- \emph{Controlon}.]
  The mechanism \Ctl~denotes control and feedback systems: classical PID
  controllers, modern state-space controllers, and feedback architectures that
  adjust actions based on error or state estimates. The label \emph{Controlon}
  derives from English \emph{control}, itself from Old French
  \emph{contrerolle} (``a register, a counter-roll'') and Medieval Latin
  \emph{contrarotulus}. In OPT usage, \emph{Controlon} refers to systems whose
  defining operation is closed-loop regulation around a target, rather than
  learning a model, performing search, or conducting probabilistic inference.

  \item[\textbf{Swm} --- \emph{Swarmon}.]
  The mechanism \Swm~comprises swarm and collective-behavior systems:
  particle-swarm optimization, ant-colony optimization, boids-like flocking,
  and other methods based on many simple agents following local rules. The
  label \emph{Swarmon} blends English \emph{swarm}, from Old English
  \emph{swarma} (``a mass of bees or other insects in motion''), with the
  \emph{-ion/-on} particle suffix. A \emph{Swarmon} system is characterized by
  emergent behavior from populations of locally interacting units, rather than
  global parametric learning or a single, centralized search procedure.

\end{description}

Taken together, these labels provide a mnemonic and etymologically grounded
lexicon for referring to OPT mechanisms at a slightly more narrative level
than the three-letter codes. They are intended as aids to memory and
exposition; the formal taxonomy remains defined in terms of the canonical
roots \Lrn, \Evo, \Sym, \Prb, \Sch, \Ctl, and \Swm.

