On-policy MCTS combined with deep learning to train an actor-critic neural network that plays Hex (Con-tac-tix).

Implementation of different On-Policy and Off-Policy Policy Gradient Methods

Containing a custom-built Reinforcement Learning environment and implementations of key RL algorithms like Q-learning and SARSA, tested in scenarios such as a drone navigation challenge and the Frozen Lake environment.

My content of CS294 Deep Reinforcement Learning course, conduced by Sergey Levine from UC Berkeley.

Stock Portfolio Management using tabular and deep Q-learning methods - extension of FinRL repo

Repository containing basic algorithm applied in python.

Monte Carlo Search Tree for training shared Actor-Critic-Network on the game Hex🏋️

PyTorch implementation of V-MPO

Reinforcement learning, Policy Gradient, Actor-Critic, AC, Agent-based Simulation, Simple-world

Reinforcement Learning Tutorial (强化学习教程)

This repository contains all of the Reinforcement Learning-related projects I've worked on. The projects are part of the graduate course at the University of Tehran.

This repository contains the implementation of a wide variety of Reinforcement Learning Projects in different applications of Bandit Algorithms, MDPs, Distributed RL and Deep RL. These projects include university projects and projects implemented due to interest in Reinforcement Learning.

Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO)

Deep Reinforcement Learning by using Truly Proximal Policy Optimization in Tensorflow 2 and Pytorch

Baseline implementation of recurrent PPO using truncated BPTT

Clean baseline implementation of PPO using an episodic TransformerXL memory