University group project concerning the implementation of an iterative learning controller tested on a Cart-Pole system. The code has been implemented in Matlab.

Disentangling Sources of Uncertainty for Active Exploration (Reinforcement Learning)

C# source code for simulation of the cart and pole balancing task.

Comparative study: Quantum vs. classical models for Cart Pole. Examining entanglement layers and data re-uploading, highlighting quantum model superiority.

A simple DQN implementation in Unity3D.

Cart pole balancing

first attempts on deep RL techniques

Using Genetic programming for sloving balancing double pendulum problem. The works demonstrates the difference of control performance by using non-Markov and Markov decision process

Modern applied deep learning with reinforcement methodology.

A simple fully connected network can be learned by genetic algorithm.

Q Learning model for a cart-pole problem

Collection of examples for Reinforcement Learning

Q_learning for cart pole

This repo implements the REINFORCE algorithm for solving the Cart Pole V1 environment of the Gymnasium library using Python 3.8 and PyTorch 2.0.1.

This repository contains a series of experiments and some theory related to reinforcement learning.

A real-time simulator of the cart-pole control system.

Matlab codes for learning Robotics

This is my implementation of Q-Learning on a cart-pole system using OpenAI Gym