Repository for most of the code from my YouTube channel
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Updated
Jul 24, 2023 - Python
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.
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
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
Cat-and-Mouse game with Reinforcement Learning (Q-Learning).
An implementation of main reinforcement learning algorithms: solo-agent and ensembled versions.
Using Q-Learning Control for path planning of mobile agents in an enviroment.
path planning using Q learning algorithm
Mountain Car problem solving using RL - QLearning with OpenAI Gym Framework
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
Reinforcement Learning Course Project - IIT Bombay Fall 2018
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
Simulation of the classic game Bomberman using Q-Learning algorithm
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.
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