Implementation of the DDPG algorithm to solve Continuous Control Reacher Environment
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Updated
Jan 26, 2019 - Jupyter Notebook
Implementation of the DDPG algorithm to solve Continuous Control Reacher Environment
Actor Critic approach for solving Reacher - Unity environment with continuous control
Deep Reinforcement Learning Project 2
Contains PyTorch Implementation of the following off policy actor critic algorithms
The DDPG algorithm incorporates Actor-Critic Deep Learning Agent for solving continuous action reinforcement learning problems.
Weakly supervised RL with safety cages for autonomous highway driving
DQN with Prioritized Experience Replay, DDPG for Continous Environments, DDPG for Multi-Agent Reinforcement Learning
Personal Collection of Reinforcement Learning Algorithms. So far: Parallelized DDPG,...
Learning to play tennis from scratch with AlphaGo Zero style self-play using DDPG
Mujoco Hopper agent with DDPG
A Deep Reinforcement Learning (DeepRL) package for RL algorithm developers.
Udacity's Deep Reinforcement Learning course
RL agent trained from scratch using DDPG+HER to perform robotic arm manipulation
Deep Deterministic Policy Gradient implementation for Reinforcement Learning course taught at Aalto University.
Lightweight deep RL Libraray for continuous control.
Reinforcement Learning - PyTorch: Continuous Control of Double Joint Robot Arm using DDPG algorithm
Simulated Portfolio Optimization (GBM & DDPG)
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