The Backend for the Morpho Design Explorer Project.
-
Updated
May 29, 2024 - Python
The Backend for the Morpho Design Explorer Project.
Statistical Machine Intelligence & Learning Engine
A simple AI in pure c++ to play the snake game
A Rust framework supporting a variaty of evolutionary computation (EC) tools
A simulation of the MBTA Subway
This course covers the applied side of algorithmics in machine learning and deep learning, focusing on hands-on coding experience in Python.
Evolutionary decision tree classifier
Welcome to AI-GameOptimization, a repository dedicated to exploring and implementing various optimization algorithms to solve complex games. This project initially focuses on solving the classic game Sokoban using the Q-learning algorithm, with plans to extend to genetic algorithms and other optimization techniques in the future.
A simple Genetic Algorithm framework
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.
What I'm learning/practicing
Python library for evolutionary and swarm intelligence algorithms.
Distributed High-Performance Symbolic Regression in Julia
Web implementation of Roger Alsing's EvoLisa problem
Artificial Neural Networks trained by a Genetic Algorithm to play Pong.
C++ Large Scale Genetic Programming
This project was presented for the Artificial Intelligence course for the academic year 2022/2023. It explores various methods to solve the N-Queens problem, including Random Search, Backtracking, Hill-Climbing, Simulated Annealing, and Genetic Algorithms. Each method is evaluated for its efficiency and effectiveness in finding solutions.
Add a description, image, and links to the genetic-algorithm topic page so that developers can more easily learn about it.
To associate your repository with the genetic-algorithm topic, visit your repo's landing page and select "manage topics."