A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
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Updated
Apr 8, 2021 - Python
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
Deep Reinforcement Learning for Trading
Actor Critic using Kronecker-Factored Trust Region
Solving CartPole-v1 environment in Keras with Actor Critic algorithm an Deep Reinforcement Learning algorithm
Official repository for the paper "Exploring the Promise and Limits of Real-Time Recurrent Learning" (ICLR 2024)
a collection of python notebooks using RL agents to play Atari games in OpenAI gym environments
Design and training of an RL agent to control a Quadcopter using Actor-Critic RL method
Topics in Machine Learning @ IIIT Hyderabad (Fall 2021)
Deep Reinforcement Learning: Continuous Control. Solve the Unity ML-Agents Reacher Environment.
Objective Stimuli Active Repeater
This repository contains high quality and tested implementation of Asynchronous Actor Critic Algorithm
A model to control a double-jointed arm to reach target using Deep Deterministic Policy Gradients
Implemented the Actor-Critic method using TensorFlow to train an agent on the Open AI Gym CartPole-V0 environment.
Implementations of some of the most well known Deep Reinforcement Learning algorithms
Fun with Reinforcement Learning in my spare time
Programming Assignments for Reinforcement Learning Specialization
Deep Reinforcement Learning: On-Policy Actor Critic methods. An implementation of Advantage Actor-Critic (A2C) and Proximal Policy Optimization (PPO) on the PyTorch Lightning framework.
unRL (AKA "unreal") is a set of libraries providing Reinforcement Learning algorithms implemented in PyTorch or Jax.
Example VPG implementation with ReLAx
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