configs

OpenEvolve Configuration Files

This directory contains configuration files for OpenEvolve with examples for different use cases.

Configuration Files

default_config.yaml

The main configuration file containing all available options with sensible defaults. This file includes:

• Complete documentation for all configuration parameters
• Default values for all settings
• Island-based evolution parameters for proper evolutionary diversity

Use this file as a template for your own configurations.

island_config_example.yaml

A practical example configuration demonstrating proper island-based evolution setup. Shows:

• Recommended island settings for most use cases
• Balanced migration parameters
• Complete working configuration

island_examples.yaml

Multiple example configurations for different scenarios:

• Maximum Diversity: Many islands, frequent migration
• Focused Exploration: Few islands, rare migration
• Balanced Approach: Default recommended settings
• Quick Exploration: Small-scale rapid testing
• Large-Scale Evolution: Complex optimization runs

Includes guidelines for choosing parameters based on your problem characteristics.

Island-Based Evolution Parameters

The key new parameters for proper evolutionary diversity are:

database:
  num_islands: 5                      # Number of separate populations
  migration_interval: 50              # Migrate every N generations  
  migration_rate: 0.1                 # Fraction of top programs to migrate
  # island_initial_programs: [null, "seeds/greedy.py"]  # Optional per-island starting programs

Parameter Guidelines

• num_islands: 3-10 for most problems (more = more diversity)
• migration_interval: 25-100 generations (higher = more independence)
• migration_rate: 0.05-0.2 (5%-20%, higher = faster knowledge sharing)
• island_initial_programs: Start islands from different programs, e.g. distinct algorithmic approaches. Entry i is the program island i starts from; null or a missing entry keeps the default (the island starts empty and takes its first parent from the other islands). Entry 0 must be null, because island 0 always starts from the initial program given on the command line, and the list may not be longer than num_islands. Relative paths resolve against the config file's directory. Each seed is evaluated once at the start of a fresh run; resuming from a checkpoint does not add them again.

When to Use What

• Complex problems → More islands, less frequent migration
• Simple problems → Fewer islands, more frequent migration
• Long runs → More islands to maintain diversity
• Short runs → Fewer islands for faster convergence

Usage

Copy any of these files as a starting point for your configuration:

cp configs/default_config.yaml my_config.yaml
# Edit my_config.yaml for your specific needs

Then use with OpenEvolve:

from openevolve import OpenEvolve
from openevolve.config import Config

config = Config()
config.from_yaml("my_config.yaml")
evolve = OpenEvolve(
    initial_program_path="program.py",
    evaluation_file="evaluator.py", 
    config=config
)