Website for the annual Genetic Programming Theory & Practice workshops
-
Updated
May 23, 2024 - HTML
Website for the annual Genetic Programming Theory & Practice workshops
A fast and simple C++ library of Genetic Algorithms only for real domain (float), useful for nonlinear optimization with constraints
A (still growing) paper list of Evolutionary Computation (EC) published in some (rather all) top-tier (and also EC-focused) journals and conferences. For EC-focused publications, only Parallel/Distributed EC are covered in the current version.
OptFrame - C++17 (and C++20) Optimization Framework in Single or Multi-Objective. Supports classic metaheuristics and hyperheuristics: Genetic Algorithm, Simulated Annealing, Tabu Search, Iterated Local Search, Variable Neighborhood Search, NSGA-II, Genetic Programming etc. Examples for Traveling Salesman, Vehicle Routing, Knapsack Problem, etc.
EC-KitY is a scikit-learn-compatible Python tool kit for doing evolutionary computation.
This course covers the applied side of algorithmics in machine learning and deep learning, focusing on hands-on coding experience in Python.
Genetic Programming library in Python
Evolutionary Algorithms Framework
Select materials to output molecules similar to the target molecule with MCTS Solver and Genetic Programming.
XCSF learning classifier system: rule-based online evolutionary machine learning
Ai Game Engine, used in a competition against other AIs by playing the Tafl Games
Implementation of data mining methods that use evolutionary algorithms
Common machine learning algorithm implementations
C++ Large Scale Genetic Programming
Automated modeling and machine learning framework FEDOT
Evolutionary Computation: A Modern Perspective ---> This is a free online book, which is actively updated now (from 2023 to 2027).
Jenetics - Genetic Algorithm, Genetic Programming, Grammatical Evolution, Evolutionary Algorithm, and Multi-objective Optimization
A Hybrid between Grammar-Guided and Strongly-Typed Genetic Programming in Python
Re-implementation of GP-GOMEA that attempts to be simpler to understand and use than the original.
Symbolic regression of physical models via Genetic Programming.
Add a description, image, and links to the genetic-programming topic page so that developers can more easily learn about it.
To associate your repository with the genetic-programming topic, visit your repo's landing page and select "manage topics."