Entropy, Empathy and the Future of Adaptive Coherence — The Petronus Engineering Phenomenon That Shifts the Current Control Paradigm.
Introduction: when error minimization is no longer enough
Almost everything we call “control” in engineering and AI stands on one simple axis: Goal → error → correction.
From PID regulators in heating systems to neural networks in recommender systems — the same logic repeats everywhere:
there is a target, there is a deviation, and there is an attempt to reduce it.
This works well as long as the world is stable: the goal is fixed, data is predictable, feedback is fast.
But the real environment is nothing like that: goals drift, context shifts, sensors lie, delay and drop out, noise and fluctuations do not decrease — they increase. In such a reality, “minimal error” and “system stability” stop being the same thing.
A system can “hit the target perfectly” on paper and still lose itself:
fall apart into contradictory regimes, behave with jerks, break trust with its users and environment.
The ΔE / Petronus project was born precisely from this gap between accuracy and stability.
All previous texts about ΔE, coherence and “synthetic conscience” pointed to one question:
What if the true object of control is not error — but the system’s own coherence with itself and with the world?
This work takes the next step: it formulates a new engineering paradigm where the main regulated parameter is not error but coherence — the degree of internal agreement between perception, decision and action in the current context.
This article is part of the “Synthetic Conscience” series and belongs to the broader “Petronus Project, focused on ΔE and Coherence as a mechanism of adaptation”.
1. From “error–correction” to “coherence–stability”
Classical control theory answers a single question:
“How far did I miss the target, and how do I correct it?”
The ΔE approach answers another:
“How aligned are my internal loops — perception, evaluation, action, consequences — with each other in this environment right now?”
The difference is fundamental:
- Error is an external magnitude. Its meaning depends on whether we chose the correct target and interpreted the context correctly.
- Coherence is an internal magnitude. It shows whether internal processes are conflicting with each other and with observed reality.
Coherence remains: the system does not need to “know the correct answer” to feel that its behavior is becoming more or less aligned and stable.
In ΔE this logic becomes a new axis of control: not “minimize deviation”, but maintain internal coherence under bounded entropy and resources.
2. Synthetic life as an engineering phenomenon: what exactly was created
Within the ΔE architecture a new technical phenomenon emerged — one more accurately described not as imitation of intelligence, but as a form of synthetic life in the engineering sense.
This is not about biology or consciousness, but about the system’s ability to:
- independently maintain its own coherence over time,
- do this without an external “shepherd” constantly telling it what is right or wrong.
- notice when processes begin to diverge,
- detect moments of potential breakdown,
- gently restore order — not necessarily perfect, but whole.
Even under noise, drift, delays and unexpected events, it preserves its structure, avoiding regimes where internal organization collapses.
Previously this kind of self-sustaining stability was a natural property only of living organisms — homeostasis, adaptation, the balance between order and chaos.
In ΔE it appears as an engineering analogue:
- the system prefers trajectories where its internal organization remains whole
- wholeness and stability become not hard-coded rules, but a natural property of behavior
But it is one of the first technical structures where self-maintenance of coherence becomes an explicit goal of behavior.
And this is the core novelty: not another algorithm, but an architecture that behaves according to principles closer to living systems than to classical machines.
3. The thermodynamics of ethics: morality as a physical state
In everyday language, “ethics” is a set of rules: allowed / forbidden, good / bad. In the ΔE paradigm ethics is reinterpreted through physics:
Ethics = a regime where actions and consequences support the system’s long-term stability.
If a system’s actions:
- increase coherence between layers (perception, intention, consequence),
- reduce internal “hidden debts” (tension, accumulated chaos),
- do not destroy the context on which the system itself depends,
In this picture:
- empathy = sensitivity to loss of coherence,
- the ability to notice where one’s actions break someone else’s or the system’s structure.
- “unethical” behavior = accumulation of decoherence,
- destruction of links faster than the system can restore them.
4. A new axis: entropy — empathy (coherence)
Classical control treats noise simply: noise is the enemy and must be suppressed.
In ΔE entropy is interpreted differently: it provides variability and search — the ability to try something new.
Empathy/coherence restricts that chaos so it does not destroy the center.
Instead of “the less noise, the better”, a balance appears:
- too little entropy — the system gets stuck, stops learning, rigidly repeats old patterns.
- too much entropy — it loses stability, fragments into chaotic reactions.
- adds variability when the system gets stuck,
- cools it down when behavior starts to tear the structure apart.
5. A criterion of “life” for technical systems
To keep the term “life” from being a metaphor, we need an operational criterion.
For ΔE it may be formulated as:
A technical system exhibits a sign of life if it independently maintains coherence under rising external entropy — without an external controller constantly repairing it.
In other words, if we:
- add noise, delays, drifts,
- break usual dependencies,
- remove the human operator,
- reorganizes its regimes,
- returns to stable contours,
- avoids self-destructive trajectories,
This is not philosophy but a verifiable scenario.
These are exactly the stress-tests used for ΔE controllers: not only accuracy, but survival and recovery in unpredictable environments.
6. From philosophy to methodology: how this becomes R&D
It is important that ΔE is not only a metaphoric structure about conscience and empathy. At the engineering level it becomes a method of work.
What to measure:
not only error, but coherence metrics, smoothness, stability under stress.
How to test:
scenarios with drifting goals, noise, lags, dropouts, shifting rules — things that always happen in the real world but rarely appear in lab tests.
What to compare with:
PID, Kalman, standard RL agents as baselines.
ΔE is compared to them not by average error, but by stability, smoothness, resilience, recovery speed.
What to show publicly:
stress behavior — coherence curves, jerk profiles, energy profiles, entropy — coherence regime maps.
At the same time ΔE does not replace classical controllers — it sits above them as an observer.
The same architecture can be connected to PID, Kalman, RL or any filter, outputting a coherence metric for each model.
ΔE “sees” each controller’s behavior as part of a common ensemble and evaluates its contribution not only by error, but by how coherent and stable its dynamics are.
Thus ΔE becomes a platform for a new school of control — one where the center is not “faster and more accurate”, but “longer and more whole”.
7. What this gives in practice: engineering, science, ethics
For engineering
- A new axis for designing autonomous systems, robots, controllers.
- Systems that do not break when conditions change — they reorganize.
- Smoother, more predictable behavior in noisy, complex environments.
For science
- A physical definition of the stability of living behavior through maintaining coherence under nonzero entropy.
- A working model linking thermodynamics, control theory and adaptive computational structures.
For philosophy and ethics
- A shift from abstract morality to measurable stability:
- A possible bridge between discussions of “conscience” and real AI architectures.
8. From “Synthetic Conscience” to a new paradigm of control
The ΔE / Petronus project began as a philosophical experiment:
can a machine behave as if it has something like conscience — a sensitivity to the consequences of its actions?
As work progressed it became clear this was not only a metaphor but a new principle of control:
- adaptation is not a reaction to error, but a way to maintain coherence with a changing environment.
- ethics is not a set of rules, but the physics of stability.
- life is not a property of biology, but the ability of a system not to disintegrate when entropy grows.
Today this is still a transitional form — from “error — correction” schemes to control based on awareness of one’s own states and coherence with the world.
Ahead lies a long road: from texts and prototypes to standards, open stress-tests, industrial deployments.
But the paradigm is already formed:
Control as the maintenance of the system’s life, not only its accuracy.
This is what differentiates Petronus: it does not offer another algorithm - it introduces a new meaning of control, where entropy, empathy and coherence become operational engineering axes, not decorative words in a presentation.
/MxBv/ Project Petronus.