Code for paper "基于多智能体深度强化学习的车联网通信资源分配优化"

Autonomous Navigation of UAV using Reinforcement Learning algorithms.

PyTorch implementations of algorithms from "Reinforcement Learning: An Introduction by Sutton and Barto", along with various RL research papers.

Implementation of the paper "Overcoming Exploration in Reinforcement Learning with Demonstrations" Nair et al. over the HER baselines from OpenAI

Chargym simulates the operation of an electric vehicle charging station (EVCS) considering random EV arrivals and departures within a day. This is a generalised environment for charging/discharging EVs under various disturbances (weather conditions, pricing models, stochastic arrival-departure EV times and stochastic Battery State of Charge (BOC…

Robot arm control using reinforcement learning algorithms : DDPG and TD3 with hindsight experience replay (HER)

Repository for Planar Bipedal walking robot in Gazebo environment using Deep Deterministic Policy Gradient(DDPG) using TensorFlow.

Simulation based Soft Continuum Robot Control via Reinforcement Learning

This Repository contains a series of google colab notebooks which I created to help people dive into deep reinforcement learning.This notebooks contain both theory and implementation of different algorithms.

Train a reinforcement learning agent to play a variation of Pong®

Implementation of the DDPG algorithm for Optimal Finance Trading

PyTorch implementation of the Q-Learning Algorithm Normalized Advantage Function for continuous control problems + PER and N-step Method

The project presents a drone obstacle avoidance system using Microsoft AirSim and the DDPG algorithm, training drones with LIDAR and depth sensors for improved real-time navigation. It compares the implementation of DDPG algorithm with different sensors and their combination.

Designing a control system to exploit model-free deep reinforcement learning algorithms to solve a real-world autonomous driving task of a small robot.

This repository implements the use of AI for robot tasks.

Learning Continuous Control in Deep Reinforcement Learning

La combinación más inteligente de Deep Q-Learning, Políticas de Gradiente, Actor-Crítico y DDPG utilizando PyTorch

An open-source hardware racing drone design and demonstration RL software for the artificial intelligence robotic drone race competitions

The objective is to teach robot to find and reach the target object in the minimum number of steps and using the shortest path and avoiding any obstacles such as humans, walls, etc usinf reinforcement learning algorithms.

Controlling a 7 DOF manipulator from the panda gym reacher environment using DDPG