Dqn Python Packages

tianshou

An elegant PyTorch deep reinforcement learning library.

tf-agents-nightly

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

agents

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

tf-agents

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

tensorlayer

Deep Learning and Reinforcement Learning Library for Scientists and Engineers

rainy

:umbrella: Deep RL agents with PyTorch:umbrella:

keras-rl2

Reinforcement learning with tensorflow 2 keras

fastrl

fastrl is a reinforcement learning library that extends Fastai. This project is not affiliated with fastai or Jeremy Howard.

mushroom-rl

Python library for Reinforcement Learning.

rlens

An observability-first reinforcement-learning training & benchmarking library, built on PyTorch and Gymnasium.

autonomous-learning-library

A PyTorch library for building deep reinforcement learning agents.

elegantrl

Massively Parallel Deep Reinforcement Learning. 🔥

neodroidagent

Reinforcement learning agent implementations, intended for use with the Neodroid platform

xuance

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

reinforcement-learning-keras

No description available

rllib

A lib for RL

pytorch-policy

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

machin

Reinforcement learning library

rle-python-interface

Retro Learning Environment Python Interface based on Ben Goodrich's work

dqn-ale-spaceinvaders

A Deep Q-Network (DQN) implementation for Atari Space Invaders using Gymnasium and PyTorch.

fast-rl

Important Note fastrl version 2 is being developed at fastrl. Note the link in the readme

nextdataai

nextdataAI: a Python library for solving mazes using classical algorithms (A*, BFS, DFS, Dijkstra, Greedy), reinforcement learning (QLearning, QTable, QNN, QLSTM), and novel pseudo-heuristics. Features include a neural network-based heuristic approximating Manhattan distance (NNHeuristic) and a custom SManhattan heuristic, a dataset gener

fcmadrl

Fully Cooperative Multi-Agent Deep Reinforcement Learning

toyrl

A clean reinforcement learning library