The DDPG algorithm incorporates Actor-Critic Deep Learning Agent for solving continuous action reinforcement learning problems.
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Updated
Apr 4, 2022 - Python
The DDPG algorithm incorporates Actor-Critic Deep Learning Agent for solving continuous action reinforcement learning problems.
Implementation of Policy Gradient Methods for Continuous and Discrete Action Spaces
Learning agents in oligopolies (Cournot / Stackelberg) Agent-based model
The program uses the DDPG algorithm and tf_agents library to train an agent in a custom environment called "TargetSeeker"
Teach a Quadcopter How to Fly!
Reinforcement Learning Project using DDPG
A model to control a double-jointed arm to reach target using Deep Deterministic Policy Gradients
Tennis Game play using Multi Agent DDPG - Deep Reinforcement Learning
Learning to play tennis from scratch with AlphaGo Zero style self-play using DDPG
Teach a quadcopter how to fly using reinforcement learning!
Learn how to apply reinforcement learning methods to applications that involve multiple, interacting agents. These techniques are used in a variety of applications, such as the coordination of autonomous vehicles.
DDPG algorithm applied for the double-jointed arm that can move to target locations.
Usage of Unity ML-Agents train two agents to play tennis
Basic implementation of continuous control agents trained using deep reinforcement learning. Project 2 of Udacity Deep Reinforcement Learning NanoDegree.
Implementations of Rl algorithms ranging from Q-learning to Multi-Agent RL using DDPG in unity and gym environments.
Deep Reinforcement learning based tumour localisation
DDPG Implementaion on bare tensorflow
Repo for the Deep Reinforcement Learning Nanodegree program
Multi-Agent training using Deep Deterministic Policy Gradient Networks, Solving the Tennis Environment
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