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DDPG

Implementation of DDPG (Modified from the work of Patrick Emami) - Tensorflow (no TFLearn dependency), Ornstein Uhlenbeck noise function, reward discounting, works on discrete & continuous action spaces

Install / Use

/learn @liampetti/DDPG
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Implementation of DDPG - Deep Deterministic Policy Gradient

Modified from the work of Patrick Emami: Deep Deterministic Policy Gradients in TensorFlow

Algorithm and hyperparameter details can be found here: "Continuous control with deep reinforcement learning" - TP Lillicrap, JJ Hunt et al., 2015

Tested on CartPole & Pendulum

Requirements

Gym and TensorFlow.

Modifications

  • Removed TFLearn dependency
  • Added Ornstein Uhlenbeck noise function
  • Added reward discounting
  • Works with discrete and continuous action spaces
View on GitHub
GitHub Stars64
CategoryDevelopment
Updated1y ago
Forks15

Languages

Python

Security Score

65/100

Audited on Jan 21, 2025

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