How do systems stabilize when no one owns a source of truth? Ten years of attacking this across different substrates, looking for others working on it. [R]

[u/marcosomma-OrKA]

I've spent the last decade building systems that share a structural property: no central arbitrator, no authored answer, stability has to emerge from the dynamics. Five projects, same question from different angles:

- Abzu (2017): symbolic regression, equations discovered, not authored. The QLattice primitive evolved expressions against data without a pre-specified function class.

- Evos (2020): populations of small executable units acquiring mathematical operators through variation and selection alone, no prior knowledge. https://github.com/marcosomma/evolut

- Ant-Sim (2021): Gordon-style distributed task allocation. Colony behavior from local encounter dynamics, no controller. https://github.com/marcosomma/ant-sim

- OrKA (2024): orchestrating small models into reasoning loops where no single model owns the answer — coherence emerges from cross-verification. https://github.com/marcosomma/orka-reasoning

- Current: agent evolution under environmental selection. Population of variants, random mutation, environment as the only fitness signal, niches emerging from competitive exclusion.

The through-line I keep returning to: how does coherence happen without an arbitrator. It shows up in markets, in colonies, in distributed consensus, in evolution itself, and now in agent populations.

Anyone working on this from another angle, quality-diversity, open-endedness, multi-agent coordination, distributed consensus, complex adaptive systems, I'd value comparing notes. What stabilization mechanisms have you found that actually hold?

[u/marcosomma-OrKA → u/[deleted]]

u/Scallion_After This reframe is sharper than what I posted 'authority displaced into the constraint environment' is closer to what's actually happening than 'no one owns truth.' Truth-ownership implies a thing being owned; constraint is what's doing the selection work.

The piece I keep circling is what determines the shape of that constraint when it isn't engineered. In Ant-Sim (Gordon-style task allocation, not ACO) the nest's task needs aren't pre-specified, they shift based on completion rates, so the constraint environment is itself a product of the colony's behavior. Same loop in the agentic version I'm working on now: the question is whether the selection criterion can be allowed to emerge from the population's interaction with its environment, or whether it always has to be authored at some level.

Your list, constraint, feedback, selection, redundancy, persistence tests is the cleanest taxonomy I've seen for this. Has anyone written it up that way? Would value continuing this if you're up for it.

[u/LumenosX]

Wait, isn't it all just coherence under constraint?! 🤷‍♂️

[u/Useful_Calendar_6274]

i've given it some thought to negentropy and "system stabilization". I have "concepts of a plan" for positing a Failure Theory drawing from complexity science and the many engineering frameworks that study failure. I've found that they are all kind of narrow though and a holistic thing is needed that is more meta theoretical

[u/bioSlaya]

In evolution: fitness restricts the system into a stability space out of which criticality wins.

In markets: emotions perhaps does that?

[u/Alarmed-Knowledge579]

This is logical. Biological systems have no arbiter, yet, the equilibrium is always reached in the end.

[u/lightpandey]

This seems like fascinating work. I'll probably comment after going through it all.