EvolvePy

EvolvePy is a Python module created to allow the easy creation and execution of evolutionary algorithms.

Documentation: EvolvePy's documentation.

Presentation video (Portuguese, click on the image):

Features

(Links to example using the feature)

• Allows to create complex individual generators using different strategies:
  • Crossover (one-point, n-point, mean)
  • Mutation (sum, multiplication, binary)
  • Dynamic mutation
  • Elitism
  • Randomic predation
  • Incremental evolution
• Define individuals with different chromosomes, with different types, ranges, sizes and parameters in the generator.
• Evaluate individuals using simple functions or multiple processes.
  • Fitness cache to avoid evaluate the same individual several times.
  • Fitness functions with different scores, which can be aggregated with different strategies.
  • Evaluate the same individual several times to avoid noise.
• Log the evolution data to analyze later.
• Integrations with other modules:
  • Wandb
  • Tensorflow/Keras
  • Gym
  • Unity ML Agents (using Gym)

Installation

• EvolvePy can be installed using pip:

  pip install --upgrade pip
  pip install evolvepy
  

• For install with all integrations dependecies (gym, tensorflow, wandb, gym_unity):

  pip install --upgrade pip
  pip install evolvepy[all_integrations]
  

• For installing from the repository:

  git clone https://github.com/EltonCN/evolvepy
  cd evolvepy
  pip install --upgrade pip
  pip install .
  

Examples

The "examples" folder have a lot of examples of how to use EvolvePy.

Authors

Created by students from Unicamp's Institute of Computing (IC-Unicamp) as a project for the evolutionary systems subject at ICMC-USP, taught by prof. Eduardo do Valle Simoes.

• EltonCN
• João Bonucci
• Thiago Lacerda