The Goal of )ne (of n) Emergents

Deduced from the Procedure Monism context

By Bodhangkur

Set-up (minimal axioms)

1. Universal Procedure (UP): a rule-set (constraints/forces) that continuously converts undirected momenta into locally coherent “hard-copy” analogues (emergents).

2. Emergent: a bounded, iterating solution to the UP in a local context. It is real insofar as it maintains coherent iteration (identity is not conserved; it must be re-made).

3. Contact: every update step is a contact event; repeated successful contacts generate recognisable identity.

4. Many: there are n contemporaneous emergents sharing and perturbing the same context.

The mesh of assistants

Drop n emergents on a turbulent plane of inputs. Each emergent has:

· a boundary (the confining constraint that makes it addressable),

· a store (usable gradients/energy),

· a model (compression of regularities encountered),

· an actuator (that schedules and shapes contacts).

Define a local score—call it Coherence Yield (CY):

CY = (contacts that preserve or improve the emergent’s capacity to iterate) ÷ (all contacts)

The UP doesn’t give “purposes”; it gives selection pressure: only those local procedures that keep CY > 0 persist as hard copies. Across the mesh, every emergent perturbs others; thus, each is both problem and resource to the rest—i.e., an assistant (in Finn’s usage).

Deduction: the goal of one emergent

For any single emergent among n:

1. Persistence imperative: Maintain its boundary such that successive iterations remain addressable.

2. Fit-improvement imperative: Compress recurrent structure (learn) to raise future CY.

3. Throughput imperative: Convert available gradients into ordered work that sustains the boundary and model.

4. Coordination imperative: Shape contacts with neighbours so that interference is reduced and mutual predictability increases (because neighbours are the dominant “environment”).

5. Export imperative: Externalise solved regularities (signals, scaffolds, norms, tools). This raises neighbours’ predictability, which in turn raises ’s CY (positive externality loop).

Put crisply:

Goal: Maximise lifetime Coherence Yield by perfecting local execution of the UP in one’s bounded address, which, in a multi-emergent mesh, entails assisting and being assisted.

That is Finn’s minim “Create and/or die” operationalised: to “create” here means to maintain and improve (i.e. adapt) the self-generating contact schedule (and its exports) that keeps the copy real.

Micro-protocol (what the goal looks like in action)

At each tick:

1. Sense: Sample contacts; update prediction errors.

2. Compress: Refactor model to reduce future surprise (shorter codes for stable regularities).

3. Budget: Allocate stored gradients to (a) repair boundary, (b) refine sensors/actuators, (c) build scaffolds that stabilise nearby dynamics.

4. Act: Choose the contact that maximises expected CY-gain (often by making neighbours more predictable).

5. Publish: Leave a trace (signal, groove, tool, convention) that lowers everyone’s future contact cost—including your own.

Why cooperation isn’t moral but mechanical here

· Neighbours dominate your uncertainty; their stability is your stability.

· Therefore “helping” others (standardising signals, smoothing traffic, sharing codes, building shared scaffolds) is instrumental to your CY, not an altruistic add-on.

· In a crowded mesh, the solitary maximiser loses to the mutual predictability maximiser.

Concrete images (three short vignettes)

· Biofilm: One bacterium secretes exopolymers (costly) that create a matrix. The matrix stabilises gradients and reduces shear—neighbours become more predictable; the secreter’s CY rises.

· Market stall: A vendor prints clear prices and queues customers (exported regularity); throughput increases; conflict falls; everyone’s prediction error drops; the stall persists.

· Sculpture park pathing: Laying paths where people already walk lowers future contact friction; visitors self-organise; the park (and its caretaker) iterate more smoothly.

Edge cases (and why they fit the same goal)

· Predation/competition: Predators “standardise” prey behaviour by funnelling them; prey “standardise” predators with alarm conventions. Both are mutual predictability games raising CY for the survivor.

· Ascetic withdrawal: Reducing contact channels can be a boundary-repair policy when turbulence exceeds processing capacity; it’s still CY-maximising.

· Innovation shocks: A risky export (new tool/norm) may briefly drop CY but raises it long-run by locking in a better scaffold.

Summary

Among many, the single emergent’s goal is to keep being a real copy by improving the fit of its contacts—most efficiently by making its neighbours (and thus the world it faces) more predictable.

Finn’s minims (capsule form)

· Confinement defines.

· Identity is not conserved; iteration is.

· Create and/or die.

· Assist to persist.

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