City Simulation Loop
The unified execution cycle that advances all city subsystems through time#
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.