62 Open source projects that are alternatives of or similar to Q-GridWorld

Some notebooks

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

Free Resources For Data Science created by Shubham Kumar

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

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

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

A gym environment for Stuart Armstrong's model of a treacherous turn.

Train a tic-tac-toe agent using reinforcement learning.

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..

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

A deep reinforcement learning bot that plays tetris

Reinforcement Learning at UCLA IPAM RIPS 2018

Operations Research Application Project - Flow Shop Scheduling Based On Reinforcement Learning Algorithm

tensorflow deep RL for driving a rover around

A framework for multi-agent reinforcement learning.

Playing Atari games with TensorFlow implementation of Asynchronous Deep Q-Learning

A life simulation for exploring social dynamics

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

An RL implementation in Keras

Arnold - DOOM Agent

An environment to high-frequency trading agents under reinforcement learning

Reinforcement Learning for Portfolio Management

PyTorch implementation of the implicit Q-learning algorithm (IQL)

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

Master Thesis: Limit order placement with Reinforcement Learning

Python implementation of QBSO-FS : a Reinforcement Learning based Bee Swarm Optimization metaheuristic for Feature Selection problem.

🐍 AI that learns to play Snake using Q-Learning (Reinforcement Learning)

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

Package provides java implementation of reinforcement learning algorithms such Q-Learn, R-Learn, SARSA, Actor-Critic

Autonomous Navigation of UAV using Reinforcement Learning algorithms.

A.I. plays the original 1980 Pacman using Neuroevolution of Augmenting Topologies and Deep Q Learning

Implementation of q-learning using TensorFlow

High frequency AI based algorithmic trading module.

MIT DeepTraffic top 2% solution (75.01 mph) 🚗.

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

Reinforcement Learning program that looks to be able to quickly learn to solve a Rubik's Cube

A multi agent path planning solution under a warehouse scenario using Q learning and transfer learning.🤖️

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

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

arxiv.org/abs/1803.07482

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

playing idealized trading games with deep reinforcement learning

DEEp Reinforcement learning framework

Code for our AAMAS 2020 paper: "A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry".

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

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

Play Google Chrome's T-rex game with TensorFlow

Reinforcement Learning Demos

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

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.

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

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

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.

Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.

Explorer is a PyTorch reinforcement learning framework for exploring new ideas.

Reinforcement Learning in Vrep

Multiagent reinforcement learning simulation framework - Undergraduate thesis in Mechatronics Engineering at the University of Brasília

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