3091 Open source projects that are alternatives of or similar to Pygame Learning Environment

A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.

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.

Artificial intelligence for the Snake game.

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!

Open-source simulator for autonomous driving research.

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

Grokking Deep Reinforcement Learning

An unbeatable game of Tic Tac Toe.

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High Fidelity Simulator for Reinforcement Learning and Robotics Research.

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

StarCraft II - pysc2 Deep Reinforcement Learning Examples

OpenSteer is a C++ library to help build steering behaviors for autonomous characters in games and animation.

High Fidelity Simulator for Reinforcement Learning and Robotics Research.

Code repository for the Animal AI Olympics competition

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

🏰 An exciting game of programming and Artificial Intelligence

owl-bt is editor for Behavior trees. It has been inspired by Unreal engine behavior trees in a way, that it supports special node items like decorators and services. This makes trees smaller and much more readable.

Implementation of Inverse Reinforcement Learning Algorithm on a toy car in a 2D world problem, (Apprenticeship Learning via Inverse Reinforcement Learning Abbeel & Ng, 2004)

AI research environment for the Atari 2600 games 🤖.

AI for Snake game trained from pixels using Deep Reinforcement Learning (DQN).

An open source framework for research in Embodied-AI from AI2.

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A fast Evolution Strategy implementation in Python

Gibson Environments: Real-World Perception for Embodied Agents

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.

Multiple implementations for abstractive text summurization , using google colab

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

use AI to play some games.

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

Arnold - DOOM Agent

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Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros

High-performance Vision library in Python. Scale your research, not boilerplate.

Source codes for the book "Reinforcement Learning: Theory and Python Implementation"

A 2D space exploration and mining game made with Godot and our AI framework

A3C LSTM Atari with Pytorch plus A3G design

Implementations of Reinforcement Learning Models in Tensorflow

A complete framework for Godot to create beautiful and complex AI motion. Works both in 2D and in 3D.

A C++ framework for MDPs and POMDPs with Python bindings

A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain

A course in reinforcement learning in the wild

Reaver: Modular Deep Reinforcement Learning Framework. Focused on StarCraft II. Supports Gym, Atari, and MuJoCo.

Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

StarCraft environment for OpenAI Gym, based on Facebook's TorchCraft. (In progress)

Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

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

Guided Policy Search

Resources to learn more about Machine Learning and Artificial Intelligence

Scalable, event-driven, deep-learning-friendly backtesting library