Simple Reinforcement learning tutorials

An introductory series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

DEEp Reinforcement learning framework

Arnold - DOOM Agent

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..

The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

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

Play Google Chrome's T-rex game with TensorFlow

Reinforcement Learning for Portfolio Management

A deep learning library to provide algs in pure Numpy or Tensorflow.

Accompanying code for Paperspace tutorial "Build an AI to play Dino Run"

Free Resources For Data Science created by Shubham Kumar

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

playing idealized trading games with deep reinforcement learning

An environment to high-frequency trading agents under reinforcement learning

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

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

Stock Trading Bot using Deep Q-Learning

Forex trading simulator environment for OpenAI Gym, observations contain the order status, performance and timeseries loaded from a CSV file containing rates and indicators. Work In Progress

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Demo project using tabular Q-learning algorithm

Master Thesis: Limit order placement with Reinforcement Learning

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

Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

A deep reinforcement learning bot that plays tetris

An RL implementation in Keras

Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51

A micro neural network multilayer perceptron for MicroPython (used on ESP32 and Pycom modules)