> ## Documentation Index
> Fetch the complete documentation index at: https://docs.emergent.community/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Emergent is a Python framework for building and simulating agent-based models on graph structures.

## What is Emergent?

**Emergent** is a lightweight, flexible Python framework for agent-based modeling (ABM). It lets you simulate how large-scale behaviors emerge from the local interactions of individual agents connected in a graph network.

Whether you're modeling social dynamics, distributed decision-making, opinion propagation, or any other complex adaptive system, Emergent gives you the primitives to define, run, and analyze your simulation with minimal boilerplate.

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/quickstart">
    Build and run your first simulation in minutes.
  </Card>

  <Card title="AgentModel" icon="cube" href="/concepts/agent-model">
    Learn the core abstraction at the heart of Emergent.
  </Card>

  <Card title="Graph Structures" icon="diagram-project" href="/concepts/graph-structures">
    Understand how agents are connected.
  </Card>

  <Card title="API Reference" icon="code" href="/api-reference/agent-model">
    Full reference for all classes and methods.
  </Card>
</CardGroup>

## Key concepts

| Concept                   | Description                                                                                         |
| ------------------------- | --------------------------------------------------------------------------------------------------- |
| **AgentModel**            | The central object that holds your graph, parameters, and simulation logic                          |
| **Graph**                 | A [NetworkX](https://networkx.org/) graph where each node is an agent                               |
| **Parameters**            | A key-value store controlling model behavior (graph type, node count, convergence thresholds, etc.) |
| **Initial data function** | A callable that sets each node's starting state                                                     |
| **Timestep function**     | A callable that advances the simulation one step                                                    |
| **Convergence**           | A built-in mechanism to stop the simulation when a tracked variable stabilizes                      |

## Installation

```bash theme={null}
pip install emergent
```

Or with [uv](https://docs.astral.sh/uv/):

```bash theme={null}
uv add emergent
```

<Note>
  Emergent requires Python 3.10.7 or higher.
</Note>