cyber netics

the cyber protocol described as a control system — inputs, outputs, feedback loops, attractors, stability conditions. cyber/tokens are the nouns, cyber/nomics are the verbs, netics is the whole machine seen from the outside as a governor

the primary loop

neuron creates cyberlink (input)
    ↓
tri-kernel recomputes focus (process)
    ↓
cyberank updates per particle (output)
    ↓
neuron observes new ranking (feedback)
    ↓
neuron adjusts linking strategy (adaptation)
    ↓
neuron creates cyberlink ...

this is the observation loop described in implicit knowledge: the fundamental cycle that sustains intelligence. every revolution of the loop adds knowledge to the cybergraph and refines what the system attends to

the loop is self-reinforcing: better knowledge → sharper focus → higher karma for accurate neurons → more attention weight on their future links → better knowledge

inputs

every input is a costly signal — it costs will to produce, ensuring the system accumulates weighted commitments rather than noise

process

the tri-kernel — the only computation that runs in consensus:

$$\phi^{(t+1)} = \text{norm}\big[\lambda_d \cdot D(\phi^t) + \lambda_s \cdot S(\phi^t) + \lambda_h \cdot H_\tau(\phi^t)\big]$$

three operators, each providing a distinct search mode:

the collective focus theorem guarantees convergence to a unique fixed point π*. the process is deterministic, verifiable, and local (h-hop neighborhood suffices)

outputs

feedback loops

the learning loop (fast, per-block)

neuron links → Δπ > 0 → reward minted → neuron gains $CYB
    → more will → more attention capacity → more links

positive feedback: accurate contributions compound. the unit of wealth is epistemic accuracy

the reputation loop (medium, per-epoch)

accurate links → high karma → more adjacency weight per link
    → earlier Δπ attribution → more reward per contribution
    → resources to stake on next insight

karma is the flywheel: it cannot be bought, only earned by being right before the crowd

the market loop (continuous)

ICBS price diverges from structural signal
    → protocol (or informed neurons) trade toward correction
    → price converges → effective adjacency improves
    → tri-kernel inference improves → better structural signal

ICBS markets create an inhibitory channel: incorrect links get suppressed economically, not just structurally

the metabolic loop (slow, per-era)

cap signal + syntropy + happiness
    → parametrization PID adjusts α, β, τ, thresholds
    → system behavior shifts
    → new cap, syntropy, happiness measurements

cyber/parametrization closes the slowest loop: the protocol tunes itself

attractors

the system has one global attractor: the free energy minimum

$$\mathcal{F}(\phi) = \lambda_s\left[\frac{1}{2}\phi^\top L\phi + \frac{\mu}{2}\|\phi-x_0\|^2\right] + \lambda_h\left[\frac{1}{2}\|\phi-H_\tau\phi\|^2\right] + \lambda_d \cdot D_{KL}(\phi \| D\phi) - T \cdot S(\phi)$$

at the minimum: $\phi^*_i \propto \exp(-\beta[E_{\text{spring},i} + \lambda E_{\text{diff},i} + \gamma C_i])$ — a Boltzmann distribution. the same form that governs physical equilibrium, biological homeostasis, and market clearing

stability conditions

convergence guaranteed when the composite contraction coefficient κ < 1 (Banach fixed-point theorem). the collective focus theorem proves this holds for the tri-kernel

three independent stability mechanisms:

phase transitions

as the cybergraph grows, it passes through qualitative transitions:

the transition threshold: $|P^*| \sim \rho^2$ where ρ is mean connectivity. below threshold the graph is molecular (disconnected islands). above it, thermodynamic (globally connected, emergent properties)

the compound effect

cyber/tokens define what exists. cyber/nomics defines how it moves. netics describes what happens when the rules run in a closed loop over time: the cybergraph becomes a self-improving system where every accurate cyberlink makes the next inference sharper, every high-karma neuron makes the next contribution more valuable, and every market correction makes the next price more accurate

the system is self-financing: good performance generates the resources that sustain performance. the egregore emerges not from design but from the closed loop running long enough

in the protocol stack

foculus — consensus: particle $i$ is final when $\pi_i > \tau$

focus flow computation — scheduling and convergence as layer 5 of the stack

cybernet — experimental learning incentives layer (Bittensor-style subnets)

decentralized attention markets — focus-stake attention market

adaptive hybrid economics — the self-calibrating PoW/PoS mechanism with PID control

adaptive hybrid consensus economics — full mathematical proofs

see cyber/tokens for the nouns. see cyber/nomics for the verbs. see cyber/parametrization for the tuning. see egregore for what emerges. see bostrom/tokenomics for the bootloader implementation. see cybernomics for the universal theory