rainandwind1

A3C_Keras_FlappyBird

Use Asynchronous advantage actor-critic algorithm (A3C) to play Flappy Bird using Keras

Adversarial-deep-learning

ardupilot

ArduPlane, ArduCopter, ArduRover source

ball_env

blood_bowl2

Applying Reinforcement Learning to Blood Bowl

Deep-Learning-with-TensorFlow-book

深度学习开源书，基于TensorFlow 2.0实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

Deep-Reinforcement-Learning-Algorithms

This is a reconstruction of previous repository(rl-algorithms).

Fighting-game-AI-

强化学习第二次大作业

Maddpg_multiagent

RL-Algorithms

rainandwind1/Deep-Reinforcement-Learning-Algorithms

This is a reconstruction of previous repository(rl-algorithms).

rainandwind1/Fighting-game-AI-

强化学习第二次大作业

rainandwind1/Maddpg_multiagent

rainandwind1/RL-Algorithms

rainandwind1/Adversarial-deep-learning

rainandwind1/ball_env

rainandwind1/Deep-Learning-with-TensorFlow-book

深度学习开源书，基于TensorFlow 2.0实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

rainandwind1/Dive-into-DL-PyTorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

rainandwind1/FeUdal-torch

rainandwind1/ffai_2019

The Fantasy Football AI framework.

rainandwind1/go_code

learning go code

rainandwind1/GpsDrivers

Platform independent GPS drivers

rainandwind1/hierarchical_architecture

rainandwind1/learn_pytorch

rainandwind1/learn_tensorflow2.0

learning tensorflow 2.0 code

rainandwind1/Leetcode

rainandwind1/macro_policy_constrain

rainandwind1/MADDPG-reconstruct

rainandwind1/mix_policy_base_on_q

rainandwind1/ml-agents

Unity Machine Learning Agents Toolkit

rainandwind1/multiagent-particle-envs

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

rainandwind1/rainandwind1

rainandwind1/README

README文件语法解读，即Github Flavored Markdown语法介绍

rainandwind1/relation_network

rainandwind1/RL-paper

rainandwind1/RL_experiments

RL experiments for RL class

rainandwind1/RL_homework_1

rainandwind1/RL_retrieval

rainandwind1/smac

SMAC: The StarCraft Multi-Agent Challenge

rainandwind1/ultimate-go

Ultimate Go study guide, with heavily documented code and programs analysis, all in 1 place