Repository for most of the code from my YouTube channel

Implementation of Q-learning algorithm and Feedback control for the mobile robot (turtlebot3_burger) in ROS.

强化学习算法库，包含了目前主流的强化学习算法(Value based and Policy based)的代码，代码都经过调试并可以运行

Code repository for my course on the fundamentals of reinforcement learning

A solution for Dynamic Spectrum Management in Mission-Critical UAV Networks using Team Q learning as a Multi-Agent Reinforcement Learning Approach

An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations using Multi Independent Agent Reinforcement Learning

Use Deep Q-Learning model to optimize energy consumption of a data center

Cat-and-Mouse game with Reinforcement Learning (Q-Learning).

Implementation of RL in the cloud for energy minimization due to migration and excess power consumption.

Using Q-Learning Control for path planning of mobile agents in an enviroment.

Indoor navigation using deep Q reinforcement learning

An implementation of main reinforcement learning algorithms: solo-agent and ensembled versions.

Deep Reinforcement Learning navigation of autonomous vehicles. Implementation of deep-Q learning, dyna-Q learning, Q-learning agents including SSMR(Skid-steering_mobile robot) Kinematics in various OpenAi gym environments

path planning using Q learning algorithm

Collection of Machine Learning Algorithms

Mountain Car problem solving using RL - QLearning with OpenAI Gym Framework

Reinforcement Learning Course Project - IIT Bombay Fall 2018

It contains a python-based survival analysis model to study the lifetime of machines in a 3-unit flowline production system, The simulation environment to be used with the RL algorithm for maintenance planning, Q-learning algorithm based maintenance policy, corrective and preventive maintenance policy simulations for comparison.

Taxi-v2 game using Q learning algorithm

Solving MountainCar-v0 environment in Keras with Deep Q Learning an Deep Reinforcement Learning algorithm

[2019 project] Using deep reinforcement learning to train AIs to play TRON

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.

Simulation of the classic game Bomberman using Q-Learning algorithm

The homework for Cutting-Edge of Deep Learning, aka CEDL, from NTHU

用QLearing增强学习算法玩拼图游戏

Developed By "Perfect Cube" - https://doi.org/10.36948/ijfmr.2025.v07i01.34840

This Repository Consists All Courses, Projects and Online Learning Done in Context of Machine learning, Data Sceince And Deep Learning From Various Sources like Youtube, Coursera, Udemy And WEbsites like Scikit, Keras

Q-Learning and Deep Q-Learning Demo

Using pygame to create a 2d pong game, then using gym and tensorflow to read the pixels on the screen using a CNN and then model the actions with a Qlearning RNN to beat the ai opponent

Implementation of Deep Q-Learning to Learn how to play a simple game written in python.