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adaptive-traffic-signal-control-using-reinforcement-learning

This is an application exploiting principles of Deep Reinforcement Learning. The Deep Neural Network is trained to approximate the Bellman Equation (Q-Learning).

ai-blog

Accompanying repository for Let's make a DQN / A3C series.

ai-for-beginners

12 Weeks, 24 Lessons, AI for All!

algo

数据结构和算法必知必会的50个代码实现

analytics-zoo

Distributed Tensorflow, Keras, PyTorch and BigDL on Apache Spark

apollo

An open autonomous driving platform

awesome-scalability

The Patterns of Scalable, Reliable, and Performant Large-Scale Systems

book_deeplearning_in_pytorch_source

boosting-gbdt

采用gbdt算法预测交通流量

branch-and-bound

A collection of utilities for implementing branch-and-bound with DFS, BrFS, BFS, and CBFS

cityflow

A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

compile-based-on-mongodb-and-cpp

编译Mongo-cxx-driver,boost_1_67_0,scons，生成C++调用的dll，开发基于C++的MongoDB数据库操作代码

cplusplusthings

C++那些事

data_diagnose

identify data latency, data miss, data anomaly in traffic data, HMM, EM

deep-qlearning-agent-for-traffic-signal-control

A framework where a deep Q-Learning Reinforcement Learning agent tries to choose the correct traffic light phase at an intersection to maximize traffic efficiency.

deep_learning_algo

常用的深度学习算法和机器学习算法，用scikit、keras和tensorflow编写

deeprl_signal_control

multi-agent deep reinforcement learning for large-scale traffic signal control.

design_pattern

常用的设计模式，common design pattern completed by python

dig-into-apollo

Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.

easy-rl

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

effectivepython

Effective Python: Second Edition — Source Code and Errata for the Book

effectivepython_test

learn effctive python book(version2)

flask

flow

Computational framework for reinforcement learning in traffic control

free-programming-books

:books: Freely available programming books

gym

A toolkit for developing and comparing reinforcement learning algorithms.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

intellilight

IntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control

little-tsp

A C++ implementation of the branch and bound TSP algorithm described by Little et al in their 1963 paper