Genetic Programming: Benchmarking Deep Memory Tasks

An adventure into "Genetic Programming" for Nigel O'Neill. Building a program that randomly 'evolves' code to solve a problem.

A proof-of-concept of using DEAP as an optimization driver for OpenMDAO.

Cryptocurrency wallet management using numerical optimisation

Delta- & Adaptive-MOCK implementation in Python

Chaos implementation to improve standart PSO performance

DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. In this project, a GA is used to calculate a graph distances.

Experimenting with various neural network configurations and genetic algorithm parameters

The paper investigates Genetic Algorithms (GAs) for extractive summarization, aiming for efficiency compared to deep learning.

Genetic algorithm applied on an shredded image to put it back into its original form, using DEAP and blackbox library.

This simple script is an example of genetic algorithm application

Make adversarial images of characters

Implementation of genetic algorithm for iterated prisoner's dilemma strategy development.

Three implemented evolutionary strategies using DEAP to optimize energy scheduling tasks.

Feature Selection for Learning To Rank with Multi Objective Genetic Algorithms

This application generates dream list-based shopping suggestion lists and how much you can spend on that purchase. #Artificial Intelligence

Chess simulation with use of evolutional algorithms

Source code used to evaluate the combination of Genetic Programming and Hyper-Heuristics to the Network Intrusion Detection problem, for the COS700 module at the University of Pretoria.

Solving a binary classification problem, using a Genetic Algorithm to optimize a Neural Network's architecture.

Resolución de un rompecabezas haciendo uso de programación genética, por medio de la herramienta DEAP