AI Agent · Models outcomes first

Simulation Agent

Models possible outcomes and tests strategies before execution.

What the Simulation Agent Does

The Simulation Agent models possible outcomes and tests strategies before execution. It runs scenarios so the swarm can choose the strongest path first.

Why It Matters

It lets the system think before it acts. Testing options in simulation is cheaper and safer than learning only in production.

Flow

Inputs and Outputs

Inputs

  • A decision or strategy to test
  • Relevant history and constraints
  • Scenarios to model
  • Success criteria

Outputs

  • Modeled outcomes per scenario
  • Surfaced risks
  • A recommended path
  • Inputs for planning

Example

Example Use Cases

Where it shows up

  • Scenario testing
  • Strategy modeling
  • Risk forecasting
  • Comparing alternative plans

Common Failure Modes

When this agent breaks

  • Models too simple to trust
  • Acting on unvalidated simulations
  • Simulating instead of acting
  • Ignoring results under pressure

In the Hierarchy

Parent Layer

Layer 06

Simulation Layer

The Simulation Layer models possible outcomes and tests strategies before the swarm commits real resources to them.

Swarm Loop

Stages It Works In

Stage 1

Define Stage

Clarify the goal, constraints, and definition of done.

Nearby

Agents It Works With

Remembers and retrieves

Memory Agent

Manages short-term, long-term, and compressed memory; controls storage and retrieval.

Turns goals into plans

Planner Agent

Converts goals into executable plans, selects strategies, defines workflows, and adapts when conditions change.

See the Simulation Agent in Action

Run a live mission to watch this agent coordinate with the rest of the swarm, or browse every agent type in the index.

Launch Simulator All Agent Types
Delivery AgentSwarm Loop