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
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
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
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
Taxi-v2 game using Q learning algorithm
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.
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.
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