352 Open source projects that are alternatives of or similar to DI-star

Using self-play, MCTS, and a deep neural network to create a hearthstone ai player

We reproduced DeepMind's results and implement a meta-learning (MLSH) agent which can generalize across minigames.

Trading Environment(OpenAI Gym) + DDQN (Keras-RL)

Deep Reinforcement Learning Pong Agent, King Pong, he's the best

Deep reinforcement learning model implementation in Tensorflow + OpenAI gym

🖥️ CS446: Machine Learning in Spring 2018, University of Illinois at Urbana-Champaign

This is a practical resource that makes it easier to learn about and apply Practical Deep Reinforcement Learning (DRL) https://ibrahimsobh.github.io/Practical-DRL/

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

Awesome RL: Papers, Books, Codes, Benchmarks

A curated list of awesome Deep Reinforcement Learning resources.

(AAAI 2018) Action Branching Architectures for Deep Reinforcement Learning

PyTorch implementation of Soft Actor-Critic (SAC)

Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch

⏪ New stats with the old client.

Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks

Deep Reinforcement Learning for Fixed-Wing Flight Control with Deep Q-Network

Modularized Implementation of Deep RL Algorithms in PyTorch

SeqGAN but with more bells and whistles

Code accompanying the blog post "Deep Reinforcement Learning with TensorFlow 2.1"

JAX implementations of core Deep RL algorithms

Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender systems

AI项目（强化学习、深度学习、计算机视觉、推荐系统、自然语言处理、机器导航、医学影像处理）

Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch

The page of the Ural Federal University course "Reinforcement Learning and Neural Networks"

Repository for codes of 'Deep Reinforcement Learning'

Minimal and Clean Reinforcement Learning Examples

Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

Remove watermark automatically(Just can use for fixed position watermark till now). 自动水印消除算法的实现（目前只支持固定水印位置）。

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

☔ Deep RL agents with PyTorch☔

playing idealized trading games with deep reinforcement learning

UAV Obstacle Avoidance using Deep Recurrent Reinforcement Learning with Temporal Attention

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

Reinforcement Learning for Super Mario Bros using A3C on GPU

Actor-critic with experience replay

Reinforcement Learning algorithm's using google-colab

Manage your machine learning experiments with trixi - modular, reproducible, high fashion. An experiment infrastructure optimized for PyTorch, but flexible enough to work for your framework and your tastes.

Functional Reinforcement Learning in Scala.

文件 笔和线段的一种划分.py,只需要把k线high，low数据输入，就能自动实现笔，线段，中枢，买卖点，走势类型的划分了。可以把sh.csv 作为输入文件。个人简历见.pdf。时间的力量。有人说择时很困难，有人说选股很容易，有人说统计套利需要的IT配套设施很重要。还有人说系统有不可测原理。众说纷纭。分布式的系统，当你的影响可以被忽略，你才能实现，Jiang主席所谓之，闷声发大财。

A simple example of how to implement vector based DQN using PyTorch and a ML-Agents environment

Summaries of machine learning papers

No description or website provided.

A binary release of trained deep reinforcement learning models trained in the Atari machine learning benchmark, and a software release that enables easy visualization and analysis of models, and comparison across training algorithms.

Combining deep learning and reinforcement learning.

A reinforcement learning package for Julia

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

"Continuous Deep Q-Learning with Model-based Acceleration" in TensorFlow

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-for-Dialogue-Generation-in-tensorflow

Research into controllers for 2d and 3d Active Ragdolls (using MujocoUnity+ml_agents)

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

Deep Reinforcement Learning (DQN) based Self Driving Car Control with Vehicle Simulator

Noisy Networks for Exploration

Ape-X DQN & DDPG with pytorch & tensorboard

31 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

A Universal Deep Reinforcement Learning Framework

Code and data for "Deep Reinforcement Learning of Marked Temporal Point Processes", NeurIPS 2018