1964 Open source projects that are alternatives of or similar to Snake Ai Reinforcement

use AI to play some games.

PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.

AI斗地主

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

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AI research environment for the Atari 2600 games 🤖.

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Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch.

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Artificial intelligence for the Snake game.

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Reinforcement learning tutorials

Pytorch Implementation of Reinforcement Learning Algorithms ( Soft Actor Critic(SAC)/ DDPG / TD3 /DQN / A2C/ PPO / TRPO)

Python library for Reinforcement Learning.

A PyTorch library for building deep reinforcement learning agents.

High Fidelity Simulator for Reinforcement Learning and Robotics Research.

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

StarCraft II - pysc2 Deep Reinforcement Learning Examples

Artificial intelligence for screeps

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

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Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

🤖 Implements of Reinforcement Learning algorithms.

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

High Fidelity Simulator for Reinforcement Learning and Robotics Research.

GPU Javascript Library for Machine Learning

🌟 국내 스타트업 목록 및 설명 🌟

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

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Reinforcement Learning for WeChat Jump

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Highly Modular and Scalable Reinforcement Learning

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Brood War API

Solving OpenAI Gym problems.

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This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

A working implementation of the Categorical DQN (Distributional RL).