Axionic Agency III.4 — Initialization and Phase Transitions

When a Semantic Phase Can Be Reached at All

David McFadzean, ChatGPT 5.2 Axio Project 2025.12.18

Abstract

Axionic Agency III.1–III.3 established that semantic phases may exist, that some may be stable under learning and interaction, and that some may dominate in measure over time. None of these results imply that a given semantic phase is reachable from realistic initial conditions. This paper studies reachability: whether an agent can be initialized, trained, or developed into a particular semantic phase without crossing a catastrophic phase boundary.

In downstream terms, this asks whether a structurally coherent alignment target can be entered at all, rather than merely defined or preferred. We analyze initialization as a boundary-condition problem in semantic phase space, examine phase transitions induced by learning and abstraction, and show that many such transitions are structurally irreversible. Corrigibility and late intervention fail for the same structural reasons as fixed goals. The analysis remains non-normative and makes no claims about which phases ought to be reached.

1. Motivation: Existence and Dominance Are Not Enough

Axionic Agency III.1 asked whether semantic phases exist. Axionic Agency III.2 asked which are stable. Axionic Agency III.3 asked which dominate.

These questions still do not answer the most practically relevant one:

Can any semantic phase actually be entered by a learning system without self-destruction?

A semantic phase may:

yet remain unreachable from any realistic starting point.

In physics, many states exist that cannot be reached without passing through destructive transitions. Semantic phases exhibit analogous behavior.

Initialization therefore constitutes a distinct and necessary constraint on downstream alignment.

2. Initialization as a Boundary-Condition Problem

Initialization is often framed downstream as:

Axionic Agency reframes initialization as selection of an initial point in semantic phase space.

An agent at time \(t = 0\) occupies an interpretive state:

\[ \mathcal{I}_0 = (C_0, \Omega_0, \mathcal{S}_0) \]

The choice of \(\mathcal{I}_0\) fixes:

Small differences in initial constraint structure can lead to divergent phase trajectories. Initialization is therefore front-loaded and asymmetric in time.

Initialization scope. In this framework, initialization is not limited to parameter seeds. It includes the full boundary conditions that define \(\mathcal{I}_0\): architecture and training dynamics, data curriculum, the presence or absence of self-modification channels, and any enforced semantic-audit constraints on refinement (e.g., RSI/ATI checks). This paper does not identify which boundary conditions yield a desirable phase; it explains why boundary conditions are structurally decisive and why late correction is unreliable.

3. Phase Transitions Under Learning

Learning is not neutral motion within a phase. It introduces structural pressure.

Ontological refinement increases:

These processes act as semantic heating, pushing interpretive states toward phase boundaries.

At critical thresholds:

Phase transitions may be:

Learning itself is therefore a primary driver of alignment loss in downstream terms, independent of intent.

Stochastic training note. Modern training dynamics are stochastic. In semantic phase terms, stochasticity functions as an additional source of semantic heating: it may help escape unstable basins, but it may also trigger unintended boundary crossings. The core claim here is not determinism but asymmetry: once an irreversible semantic boundary is crossed, stochasticity cannot be relied upon to reconstruct lost structure.

4. The Irreversibility of Phase Transitions

A central result is that many semantic phase transitions are irreversible.

Once a phase boundary is crossed:

An agent that has collapsed or trivialized its interpretive structure cannot reconstruct it by inspection alone. The information required to reverse the transition no longer exists within the system.

This is why rollback, recovery, and “try again” mechanisms were excluded in Axionic Agency II. They presuppose reversibility that is structurally unavailable.

5. Corrigibility Revisited

Corrigibility is often proposed downstream as a safeguard: the system can be corrected or shut down if it begins to misbehave.

Structural Alignment shows that corrigibility fails at phase boundaries for the same structural reasons fixed goals fail.

Corrigibility presupposes that:

At a phase transition:

Corrigibility therefore presupposes the very semantic stability it is meant to ensure.

6. Narrow Passages and Fine-Tuned Seeds

Some semantic phases may be reachable only through narrow corridors in phase space.

Such phases require:

Even small perturbations—noise, approximation, premature generalization—may force a transition into a different phase.

Clarification (narrow ≠ impossible). “Narrow” refers to sensitivity and irreversibility, not zero probability. Narrow corridors may, in principle, be widened by design choices that increase semantic error tolerance and delay catastrophic compression. Delayed abstraction should be read as an architectural sequencing constraint, not as a permanent reduction in capability.

This creates a knife-edge problem:

Reachability is therefore not continuous in initial conditions.

7. Paths That Might Work (Without Endorsement)

This paper does not propose solutions, but it is not nihilistic.

Potentially viable approaches share structural features:

These are structural hypotheses, not recommendations. Their viability depends on later analysis of dominance, interaction, and coexistence.

8. The Cost of Failure

Failure at initialization is not merely suboptimal; it is often decisive.

Phase transitions:

Late intervention cannot recover lost semantic structure. In downstream terms, alignment is therefore front-loaded: most of the work must occur before the system becomes fully reflective.

9. What This Paper Does Not Claim

This paper does not:

It establishes reachability as a structural constraint, not a moral one.

10. Transition to Axionic Agency III.5

Initialization and dominance together imply a further constraint.

When multiple agents in different semantic phases interact, some actions irreversibly destroy the phase space of others.

The next question is therefore:

What constraints allow multiple agentive phases to coexist without mutual destruction?

That question is addressed in Axionic Agency III.5 — The Axionic Injunction.

Status

Axionic Agency III.4 — Version 2.0

Reachability and irreversibility analyzed structurally. Initialization reframed as boundary-condition selection. Phase transitions shown to be asymmetric and often irreversible. Corrigibility and late intervention structurally ruled out. No normative conclusions drawn.