EPIC SIMULATION

CUSTOMER SIMULATION · POLICY TESTING

Customer Simulation for Policy Testing

Customer Simulation for Policy Testing: model how rules and interventions change incentives and system outcomes, compare scenarios, and inspect persistent state and autonomous-agent behavior in Epic Simulation.

How this scenario works

Explore customer journeys, demand, queues, choices and service outcomes under different conditions. For policy testing, the model focuses on how rules and interventions change incentives and system outcomes.

Start with explicit assumptions, change one or more conditions, preserve state history, and compare why trajectories diverge.

What to observe

  • conversion path
  • wait time
  • drop-off
  • demand response

Also inspect agent choices, resource changes, constraints, feedback loops and second-order effects.

Scenario workflow

  1. Define the system boundary and initial state.
  2. Choose actors, resources, rules and constraints.
  3. Run a baseline before changing assumptions.
  4. Apply one or more interventions or shocks.
  5. Compare state, behavior and outcome differences.
  6. Trace important outcomes back to stored events and assumptions.

A simulation is a model of possibilities, not a guarantee or proof of a real-world outcome.

Questions to test

  • Which assumptions materially change the result?
  • Where do bottlenecks, conflicts or unexpected behaviors emerge?
  • How do autonomous agents adapt as conditions change?
  • What stored evidence explains the outcome?

FAQ

What is customer simulation for policy testing?

It applies customer simulation to how rules and interventions change incentives and system outcomes.

What should this simulation measure?

conversion path, wait time, drop-off, demand response.

Does a simulation guarantee a real-world outcome?

No. A simulation explores modeled possibilities under explicit assumptions; it does not prove what will happen in the real world.

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