There are 3 repositories under deep-deterministic-policy-gradient topic.
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
A PyTorch library for building deep reinforcement learning agents.
JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
Implementation of algorithms for continuous control (DDPG and NAF).
End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo
Repository for Planar Bipedal walking robot in Gazebo environment using Deep Deterministic Policy Gradient(DDPG) using TensorFlow.
Mapless Collision Avoidance of Turtlebot3 Mobile Robot Using DDPG and Prioritized Experience Replay
scalable multi agents reinforcement learning
Reinforcement learning in JavaScript & Node.js
A Pytorch DQN and DDPG implementation for a smart home energy management system under varying electricity price.
Pytorch implementation of the Deep Deterministic Policy Gradients for Continuous Control
Implementation of Deep Deterministic Policy Gradients (DDPG) to teach a Quadcopter How to Fly!
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.
Option hedging strategies are investigated using two reinforcement learning algorithms: deep Q network and deep deterministic policy gradient.
Implemenation of DDPG with numpy only (without Tensorflow)
Multi-Agent training using Deep Deterministic Policy Gradient Networks, Solving the Tennis Environment
Version 3.0.0 Pytorch implementations of DQN, DDQN, DDPG, SAC, Discrete SAC. With more features :)
Implementing Deep Reinforcement Learning Algorithms in Python for use in the MuJoCo Physics Simulator
PyTorch framework for reinforcement learning
Various machine learning implementations and tools
DDPG Algorithm is implemented using Pytorch
Goal-conditioned reinforcement learning like 🔥
Implementation of deep deterministic policy gradient with Wolpertinger
In this project, I attempt to solve fetch and slide open gym environment with Hindsight Experience Replay and the I experiment with Prioritised experience replay to see if there are any performance improvements
Deep Deterministic Policy Gradient (DDPG) is a model-free off-policy algorithm for learning continuous actions. It is a reinforcement learning technique that combines ideas from DPG (Deterministic Policy Gradient) and DQN (Deep Q-Network). From DQN, it uses Experience Replay and Slow-learning target networks. From DPG, it incorporates Operating over continuous action spaces.
Build and test DRL algorithms in different environments
Deep Reinforcement Learning: Continuous Control. Solve the Unity ML-Agents Reacher Environment.
Code and Report relating to the Advanced Reinforcement Learning University Unit