This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)

PyTorch implementation of Trust Region Policy Optimization

Python implementation of some numerical (optimization) methods

A trading bitcoin agent was created with deep reinforcement learning implementations.

A collection of Reinforcement Learning implementations with PyTorch

Trust Region Policy Optimization (TRPO) in pure TensorFlow

Official implementation of the AAAI 2021 paper Deep Bayesian Quadrature Policy Optimization.

Benchmarking the Natural Gradient in Policy Gradient Methods and Evolution Strategies

works about solving nonlinear dynamic systems

Undergraduate Dissertation (University of Malta) 2020-2023 - 'Autonomous Drone Control using Reinforcement Learning''

My solutions to the labs from this bootcamp:

Course projects of CS395T Numerical Optimization, UT Austin

The pytorch implemetation of trpo

Scheduling TRPO's KL Divergence Constraint

Code for the ICML 2024 paper 'GFlowNet Training by Policy Gradients'

RL-Odyssey is a research framework for continuous control that implements state-of-the-art RL algorithms (SAC, TD3, PPO, etc.) with clean experiment scripts and interactive notebooks.