Modules
Jido.Evolve is a generic evolutionary algorithm framework for Elixir.
Canonical configuration structure for evolutionary algorithms.
Protocol for crossover operations between two parent entities.
Uniform crossover for map genomes.
Partially Mapped Crossover (PMX) for permutations.
Single-point crossover implementation for strings.
Uniform crossover implementation for lists.
Core evolutionary algorithm engine.
Centralized error handling for Jido.Evolve using Splode.
Configuration error class.
Error raised for invalid configuration.
Execution error class.
Error raised for execution failures.
Internal error class.
Error raised for unexpected internal failures.
Invalid input error class.
Error raised for invalid input.
Protocol for making any data structure evolvable.
Evolvable protocol implementation for hyperparameter maps.
Helper functions for working with permutation genomes.
A simple example of evolving text towards a target string.
Hyperparameter Optimization: Evolve ML model hyperparameters for best performance.
Knapsack Problem: Select items to maximize value without exceeding weight capacity.
Traveling Salesman Problem (TSP): Find the shortest route visiting all cities.
Shared utilities for Jido.Evolve examples.
Behaviour for fitness evaluation functions.
Behaviour for mutation strategies.
Adaptive text mutation strategy that adjusts mutation rate based on fitness.
Bit-flip mutation for binary genomes.
Schema-driven mutation for hyperparameter maps.
Mutation strategies for permutation genomes.
Random mutation strategy for any evolvable entity.
Text-specific mutation strategy that works directly with strings.
Canonical option validation and normalization for Jido.Evolve.evolve/1.
Behaviour for selection strategies.
Tournament selection strategy.
Represents the state of an evolutionary algorithm at a given generation.
Mix Tasks
Install and configure Jido.Evolve for use in an application.