ll-hao

RL-CBF

genshin_auto_fish

基于深度强化学习的原神自动钓鱼AI

thermoAI

Heating system control with Reinforcement Learning

multi_armed_bandit

Monte Carlo simulations of several different multi-armed bandit algorithms and a comparison with classical statistical A/B testing

pymc

Bayesian Modeling and Probabilistic Programming in Python

d3rlpy

An offline deep reinforcement learning library

BCQ

Author's PyTorch implementation of BCQ for continuous and discrete actions

tf2multiagentrl

Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x

gym-anm

Design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.

CityLearn

Official reinforcement learning environment for demand response and load shaping

realistic-ssl-evaluation

Open source release of the evaluation benchmark suite described in "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"

seed_rl

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.

comix

MAAC

Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019

PettingZoo

An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

deeprl_network

multi-agent deep reinforcement learning for networked system control.

pymarl

Python Multi-Agent Reinforcement Learning framework

pytorch-a2c-ppo-acktr-gail

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

Tensorboard2Seaborn

Plot Tensorflow Summary Event in a Beautiful Way 🌈

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

lagom

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

jmlr-style-file

LaTeX style file for the Journal of Machine Learning Research

RLexample

Some basic examples of playing with RL

Deep-reinforcement-learning-with-pytorch

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

stable-baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

CLR

Trading-Gym

A Trading environment base on Gym

Deep-Reinforcement-Learning-Algorithms-with-PyTorch

PyTorch implementations of deep reinforcement learning algorithms and environments