City Scenario Templates

Reusable narrative and execution scaffolds for city‑scale simulation scenarios#

Scenarios are structured stories told through the simulation loop.
They define what happens, when it happens, and what pressures are applied — without hard‑coding outcomes.

Scenario templates allow cities to be:

  • compared across runs
  • stress‑tested under identical conditions
  • explored across alternate futures
  • used for training, policy testing, or research

Scenarios turn the city from a model into a laboratory.


Purpose#

Scenario templates exist to:

  • standardize how scenarios are defined and executed
  • separate narrative intent from simulation mechanics
  • enable replay, comparison, and branching futures
  • support crisis, growth, collapse, and recovery modeling
  • provide AI‑legible scenario structure

Scenarios are inputs, not scripts.


Scenario as Substrate Expression#

Each scenario operates through the shared substrate:

  • Structure (S) — which systems are stressed or altered
  • Activation (E) — how intensity is injected or dampened
  • Relational Time (R) — when events occur and how long effects persist

Scenarios shape conditions, not decisions.


Canonical Scenario Template Structure#

Every scenario should follow this structure.


Scenario Identity#

Scenario Name:
Scenario Type: growth / crisis / collapse / recovery / mixed
Primary Stress Domain(s): infrastructure, population, economy, governance, information, inequality
Time Horizon: short / medium / long
Replayable: yes / no


Narrative Intent#

Describe the high‑level story the scenario explores.

Examples:

  • rapid growth under infrastructure strain
  • misinformation‑driven unrest
  • resource scarcity and governance response
  • inequality‑driven fragmentation
  • coordinated recovery after collapse

This section is human‑readable, not executable.


Initial Conditions#

Define the starting state of the city.

Include:

  • baseline regimes for each subsystem
  • resource stock levels
  • population activation state
  • governance legitimacy
  • inequality distribution

Initial conditions anchor the scenario.


Trigger Events#

Define discrete events injected into the simulation.

Examples:

  • infrastructure failure
  • economic shock
  • environmental event
  • policy change
  • information disruption

Each trigger specifies:

  • affected subsystem(s)
  • magnitude
  • timing

Ongoing Pressures#

Define sustained forces applied over time.

Examples:

  • prolonged resource scarcity
  • sustained misinformation
  • chronic underinvestment
  • demographic shift

Ongoing pressures shape trajectory, not spikes.


Intervention Windows#

Define when interventions are allowed or expected.

Examples:

  • early governance response window
  • late emergency intervention
  • recovery investment phase

Intervention timing is often more important than strength.


Success & Failure Conditions#

Define scenario evaluation criteria.

Examples:

  • stabilization achieved
  • collapse triggered
  • inequality reduced
  • legitimacy restored

Outcomes are observed, not forced.


Metrics & Observables#

Specify what is tracked.

Examples:

  • population stress index
  • economic volatility
  • infrastructure failure rate
  • trust and legitimacy
  • inequality persistence

Metrics enable comparison across runs.


Branching Conditions (Optional)#

Define conditions that alter scenario flow.

Examples:

  • if unrest exceeds threshold → emergency governance
  • if trust recovers → accelerated recovery

Branching enables non‑linear futures.


Termination Conditions#

Define when the scenario ends.

Examples:

  • time horizon reached
  • irreversible collapse
  • stable recovery achieved

Termination is a state, not a timer.


Canonical Scenario Archetypes#

Common reusable scenario families include:

  • Growth Under Strain
  • Infrastructure Shock
  • Resource Scarcity Crisis
  • Misinformation Cascade
  • Inequality Fracture
  • Governance Failure
  • Coordinated Recovery

Each archetype can be parameterized.


Scenario Execution Flow#

Scenarios execute by:

  1. Initializing city state
  2. Injecting triggers and pressures
  3. Running the city simulation loop
  4. Applying interventions when allowed
  5. Observing outcomes and metrics

Scenarios do not override the simulation loop.


Integration Notes#

Scenario templates:

  • sit above the city simulation loop
  • remain domain‑agnostic
  • enable comparison and learning
  • support AI‑driven exploration

They are the interface between intent and dynamics.


Status#

Canonical city‑scale scenario template framework.
Designed for extension by domain‑specific or narrative layers.