Tabular methods for reinforcement learning

path planning using Q learning algorithm

The following project concerns the development of an intelligent agent for the famous game produced by Nintendo Super Mario Bros. More in detail: the goal of this project was to design, implement and train an agent with the Q-learning reinforcement learning algorithm.

Demonstration of Q-Learning and SARSA algorithms utilizing Python and OpenAI GYM

Reinforcement learning algorithm implements.

This github contains a simple OpenAi Gym Maze Enviroment and (at now) a RL Algorithm to solve it.

Solutions for OpenAI Gym RL environments

Applying PBT optimization technique to different domains

Using the SARSA to beat the environment, Windy Gridworld. Implement in C++.

Implementation of certain crucial algorithms in the field of reinforcement learning.

|| Studying RL the hard way || Implementation of Important Algorithms in PyTorch from "Reinforcement Learning an Introduction" by Sutton and Barto along with RL papers

The implementation of some reinforcement learning techniques like (Q-learning, SARSA, DQN) in two assignments and one big project.

Implementation of SARSA algorithm for path planning

Reinforcement learning system using the SARSA-RL Algorithm to learn to play a simple physics game, referred to as the The Acrobat Game

Pac-Man RL Agent

Temporal Difference methods - A simple implementation of SARSA algorithm applied to OpenAI gym's "CliffWalking" environment.

This repository has been created just for warm-up in reinforcement learning and there are my simulation files of UT-RL course HWs.

人工智能课程的实验

PacmanRL - Reinforcement Learning for Pacman (Q-Learning / SARSA)

Implementation of an agent capable of playing a simplified version of the blackjack game using SARSA algorithm.