AMBER Documentation
AMBER (Agent-based Modeling with Blazingly Efficient Records) is a powerful Python framework for building and running agent-based models. It provides a comprehensive toolkit for researchers and practitioners to create complex simulations with ease.
Features
Intuitive API: Simple and clean interface for building agent-based models
High Performance: Efficient data structures using Polars for fast simulations
Flexible Environments: Support for grid, continuous space, and network topologies
Rich Analytics: Built-in data collection and analysis tools
Scalable: Handles models from small prototypes to large-scale simulations
Extensible: Easy to extend with custom agent behaviors and environments
Quick Start
Install AMBER using pip:
pip install ambr
Create your first model:
import ambr as am
class SimpleModel(am.Model):
def setup(self):
# Create 100 agents
for i in range(100):
agent = am.Agent(self, i)
self.add_agent(agent)
def step(self):
pass # Define agent behaviors here
# Run the model
model = SimpleModel({'steps': 50})
results = model.run()
For more examples, check the examples/ directory in the repository.
Table of Contents
User Guide
API Reference
Development