73 Open source projects that are alternatives of or similar to TRPO-TensorFlow

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

An elegant PyTorch deep reinforcement learning library.

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

TD-Regularized Actor-Critic Methods

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

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Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

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Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

A course on Deep Reinforcement Learning in Computer Vision. Visit Website:

Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras

A curated list of Monte Carlo tree search papers with implementations.

Multiple implementations for abstractive text summurization , using google colab

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Trust Region Policy Optimization with TensorFlow and OpenAI Gym

An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.

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Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

Deep reinforcement learning using baidu PARL(maze,flappy bird and so on)

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Highly Modular and Scalable Reinforcement Learning

This project aims to select a supervised algorithm that can predict stock prices basing on historical data and use the predictor generated to form trading strategies.

HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.

A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading

Implementations of Reinforcement Learning Models in Tensorflow

Usage of policy gradient reinforcement learning to solve portfolio optimization problems (Tactical Asset Allocation).

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

Code for "Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner" in ICCV 2017

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

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强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

[파이썬과 케라스로 배우는 강화학습] 예제

Solving board games like Connect4 using Deep Reinforcement Learning

강화학습에 대한 기본적인 알고리즘 구현

tensorflow implementation of Andrej Karpathy's blog about reinforcement learning. http://karpathy.github.io/2016/05/31/rl/

Applied Deep Learning (2019 Spring) @ NTU

No description or website provided.

Implementation of Sequence Generative Adversarial Nets with Policy Gradient in PyTorch

Mxnet implementation of Deep Reinforcement Learning papers, such as DQN, PG, DDPG, PPO

Deep Reinforcement Learning Algorithms implemented with Tensorflow 2.3

PyTorch implementation of some reinforcement learning algorithms: A2C, PPO, Behavioral Cloning from Observation (BCO), GAIL.

Combining deep learning and reinforcement learning.

Reinforcement learning tutorials