Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"

A PyTorch library for building deep reinforcement learning agents.

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

Implementation of algorithms for continuous control (DDPG and NAF).

End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo

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

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

scalable multi agents reinforcement learning

PyTorch implementation of D4PG with the SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.

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

Implementations of various RL and Deep RL algorithms in TensorFlow, PyTorch and Keras.

Goal-conditioned reinforcement learning like 🔥

Implemenation of DDPG with numpy only (without Tensorflow)

Version 3.0.0 Pytorch implementations of DQN, DDQN, DDPG, SAC, Discrete SAC. With more features :)

Multi-Agent training using Deep Deterministic Policy Gradient Networks, Solving the Tennis Environment

Various machine learning implementations and tools

Implementation of deep deterministic policy gradient with Wolpertinger

🤖 TD3 implementation for Pendulum-v1 using PyTorch. Features twin critics, delayed policy updates, target policy smoothing, and clipped double Q-learning to address function approximation errors.