City Simulation Loop

The unified execution cycle that advances all city subsystems through time#

The city simulation loop defines how the city runs.

It does not describe any single domain.
It defines how all domains update, interact, and co‑evolve across each simulation step.

This loop is the heartbeat of the city.


Purpose#

The city simulation loop exists to:

  • synchronize all city subsystems
  • enforce S/E/R coherence across updates
  • propagate activation, feedback, and transitions
  • support scenario execution and intervention testing
  • provide a canonical execution order for simulation engines

Without this loop, the city is a diagram.
With it, the city becomes a living system.


Loop as Substrate Expression#

The simulation loop itself expresses the substrate:

  • Structure (S) — persistent state variables and networks
  • Activation (E) — dynamic pressures and intensities
  • Relational Time (R) — step cadence, delays, and memory

Each iteration advances the city one coherent moment.


Canonical Loop Phases#

Each simulation step proceeds through the following ordered phases.


1. External Inputs & Shocks#

Inject exogenous influences.

Examples:

  • climate events
  • regional economic shifts
  • policy changes
  • technological disruptions

These inputs modify baseline S/E/R conditions.


2. Resource Dynamics Update#

Update resource stocks and flows.

Includes:

  • inflow and depletion
  • storage buffering
  • distribution stress

Resource constraints propagate upward into all other systems.


3. Infrastructure Regime Update#

Evaluate infrastructure capacity and strain.

Includes:

  • load vs. capacity
  • congestion and degradation
  • failure probability

Infrastructure constrains movement, energy, and access.


4. Population Activation Update#

Update collective human activation.

Includes:

  • stress accumulation
  • engagement or withdrawal
  • movement and unrest

Population activation responds rapidly to material and informational signals.


5. Economic Activation Update#

Update market intensity and volatility.

Includes:

  • transaction velocity
  • employment shifts
  • investment behavior

Economic activation translates resources and behavior into market motion.


6. Inequality Dynamics Update#

Update distributional gradients.

Includes:

  • access divergence
  • recovery asymmetry
  • stress concentration

Inequality evolves slowly but persistently.


7. Information Flow Update#

Update perception and signaling.

Includes:

  • signal propagation
  • trust modulation
  • narrative amplification

Information flow can override material signals.


8. Governance Response Update#

Evaluate institutional response.

Includes:

  • perception of conditions
  • decision latency
  • intervention deployment

Governance acts late but broadly.


9. Feedback Loop Resolution#

Apply cross‑domain feedback.

Includes:

  • stabilizing loops
  • amplifying loops
  • learning adjustments

Feedback determines whether the system settles or escalates.


10. Stability Cycle & Regime Evaluation#

Evaluate regime transitions.

Includes:

  • regime thresholds
  • stability basin shifts
  • recovery or collapse paths

This phase determines long‑arc direction.


11. State Persistence & Memory#

Commit state to memory.

Includes:

  • structural scars
  • activation sensitivity
  • temporal inertia

Memory shapes future behavior.


12. Time Advancement#

Advance simulation time.

Includes:

  • step increment
  • cycle counters
  • horizon updates

The city moves forward one coherent beat.


Loop Timing & Resolution#

The loop supports multiple time resolutions:

  • fast ticks (minutes / hours)
  • daily cycles
  • seasonal cycles
  • long‑arc steps

Different subsystems may update at different cadences within the same loop.


Intervention Points#

Interventions may be applied at:

  • resource allocation
  • infrastructure investment
  • governance policy
  • information messaging
  • inequality mitigation

Interventions alter future loop behavior, not past state.


Failure & Termination Conditions#

The loop may detect:

  • systemic collapse
  • irreversible fragmentation
  • recovery stabilization
  • scenario completion

Termination is a state outcome, not an error.


Integration Notes#

The city simulation loop:

  • binds all city subsystems
  • enforces execution order
  • preserves substrate coherence
  • enables scenario replay and comparison

This file is the bridge between theory and execution.


Status#

Canonical city‑scale simulation loop definition.
Designed for implementation in code, games, or analytical models.