Maze solving using genetic algorithms
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Updated
Nov 25, 2022 - Jupyter Notebook
Maze solving using genetic algorithms
Using Genetic programming, an Evolutionary Algorithm, to solve and research the problem of Symbolic regression analysis and Rice Classification.
This repository used to learn how genetic algorithms works.
Repository per il progetto d'esame di AOCR (UNINA).
A universal supervisor controller and ER suite for Webots that can be adapted to any wheeled robot morphology with ease. The project is also setup to allow for easy Reinforcement Learning experimentation with some select algorithms (CMA-ES, Novlty Search, MAP-Elites) and neural networks (fixed and recurrent).
Resumen de la parte práctica que abordamos en el curso de IA. Scripts correspondientes a algoritmos de búsqueda, redes neuronales artificiales y algoritmos genéticos.
Genetic programming project for Artificial intelligence class
This project was developed as a personal research project after my Master's degree. It aims to explore the intersection of quantum biology and the effects of radiation on fungal species, leveraging advanced data analysis and simulation techniques.
Using DEAP, an evolutionary algorithm, and genetic programming to solve the n-queens problem.
A research work done during my last bachelor year about optimize system to simulate epidemic propagation with Agent-Based Systems
Using Genetic programming, to evolve stategies that preditors and preys will use in a simulated environment, such that Preditors get better at catching preys over time (generations).
Evolutionary Scheduling Made Easy: an attempt to solve a common combined clustering and rostering problem with evolutionary algorithms.
Optimizations using Metaheuristics (GA, PSO, ABC...) for solving Travelling salesman Problem (38 / 194 cities) and CEC2008 benchmark functions.
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