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).
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Updated
Mar 26, 2024 - Python
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).
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.
Evolutionary Scheduling Made Easy: an attempt to solve a common combined clustering and rostering problem with evolutionary algorithms.
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).
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