Mesa Examples
Core Mesa examples
The core Mesa examples are available at the main Mesa repository: https://github.com/mesa/mesa/tree/main/mesa/examples
Those core examples are fully tested, updated and guaranteed to work with the Mesa release that they are included with. They are also included in the Mesa package, so you can access them directly from your Python environment.
Mesa user examples
This repository contains user examples and showcases that illustrate different features of Mesa. For more information on each model, see its own Readme and documentation.
- Mesa examples that work on the Mesa and Mesa-Geo main development branches are available here on the
main branch.
- Mesa examples that work with Mesa 3.x releases are available here on the
mesa-3.x branch.
- Mesa examples that work with Mesa 2.x releases and Mesa-Geo 0.8.x releases are available here on the
mesa-2.x branch.
To contribute to this repository, see CONTRIBUTING.rst.
This repo also contains a package that readily lets you import and run some of the examples:
$ # This will install the "mesa_models" package
$ pip install -U -e git+https://github.com/mesa/mesa-examples#egg=mesa-models
For Mesa 3.x examples, install:
$ # This will install the "mesa_models" package
$ pip install -U -e git+https://github.com/mesa/[email protected]#egg=mesa-models
For Mesa 2.x examples, install:
$ # This will install the "mesa_models" package
$ pip install -U -e git+https://github.com/mesa/[email protected]#egg=mesa-models
from mesa_models.boltzmann_wealth_model.model import BoltzmannWealthModel
You can see the available models at setup.cfg.
Table of Contents
Grid Space Examples
A highly abstracted, simplified model of an economy, with only one type of agent and a single bank representing all banks in an economy.
A cellular automaton model where agents opinions are influenced by that of their neighbors. As the model evolves, color patches representing the prevailing opinion in a given area expand, contract, and sometimes disappear.
A very fast performance optimized version of Conway’s Game of Life using the Mesa PropertyLayer. About 100x as fast as the regular versions, but limited visualisation (for now).
Conway’s game of life on a hexagonal grid.
A simulation of ant foraging behavior on a hexagonal grid using pheromone trails and property layers.
Simple cellular automata of a fire spreading through a forest of cells on a grid, based on the NetLogo Fire model.
This project is an agent-based model implemented using the Mesa framework in Python. It simulates market dynamics based on Hotelling’s Law, exploring the behavior of stores in a competitive market environment. Stores adjust their prices and locations if it’s increases market share to maximize revenue, providing insights into the effects of competition and customer behavior on market outcomes.
This project simulates how unpopular norms can dominate a society even when the vast majority of individuals privately reject them. It demonstrates the “illusion of consensus” where agents, driven by a fear of appearing disloyal, not only comply with a rule they hate but also aggressively enforce it on their neighbors. This phenomenon creates a “trap” of False Enforcement, where the loudest defenders of a norm are often its secret opponents.
This model simulates a humanitarian aid distribution scenario using a needs-based behavioral architecture. Beneficiaries have dynamic needs (water, food) and trucks distribute aid using a hybrid triage system.
A simple agent-based simulation showing how rumors spread through a population based on the spread chance and initial knowing percentage, implemented with the Mesa framework and adapted from NetLogo Rumor mill.
An implementation of Axelrod’s model of cultural dissemination. Agents on a grid hold multi-feature cultural profiles and interact with neighbors based on cultural similarity, producing emergent cultural regions. Demonstrates how local convergence and global polarization can coexist.
A fast-spreading pathogen outbreak model with no exposed/latency period
inspired loosely from the game Plague Inc, though the goal here is containment rather than world domination. The model simulates how quarantine
compliance rates at the population level affect outbreak dynamics,
analyzing changes in infection, death and immunity rates.
Continuous Space Examples
No user examples available yet.
Network Examples
This is the same Boltzmann Wealth Model, but with a network grid implementation.
This is based on Dorigo’s Ant System “Swarm Intelligence” algorithm for generating solutions for the Traveling Salesman Problem.
A classic synchronization problem demonstrating resource contention, deadlock, and starvation on a network graph.
Visualization Examples
A modified version of the Bank Reserves example made to provide examples of Mesa’s charting tools.
Example of grid display and direction showing agents in the form of arrow-head shape.
GIS Examples
Vector Data
Raster Data
Raster and Vector Data Overlay
Other Examples
This folder contains an implementation of El Farol restaurant model. Agents (restaurant customers) decide whether to go to the restaurant or not based on their memory and reward from previous trials. Implications from the model have been used to explain how individual decision-making affects overall performance and fluctuation.
This example applies caching on the Mesa Schelling example. It enables a simulation run to be “cached” or in other words recorded. The recorded simulation run is persisted on the local file system and can be replayed at any later point.
A continuous double-auction market with zero-intelligence traders. Buyers and sellers each have a private reservation price or cost, and submit randomized, budget-constrained bids and asks as they arrive asynchronously through Mesa’s event-driven scheduler. The order book matches on price-time priority and clears at the midpoint price, converging naturally toward the market’s theoretical equilibrium.
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