Introduction

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.

Quickstart

Build and run your first simulation in minutes.

AgentModel

Learn the core abstraction at the heart of Emergent.

Graph Structures

Understand how agents are connected.

API Reference

Full reference for all classes and methods.

Key concepts

Concept	Description
AgentModel	The central object that holds your graph, parameters, and simulation logic
Graph	A NetworkX 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

pip install emergent

Or with uv:

uv add emergent

Emergent requires Python 3.10.7 or higher.

Get Started

Core Concepts

Examples

What is Emergent?

Quickstart

AgentModel

Graph Structures

API Reference

Key concepts

Installation

​What is Emergent?

Quickstart

AgentModel

Graph Structures

API Reference

​Key concepts

​Installation

What is Emergent?

Key concepts

Installation