aldobattista Goto Github PK

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

book

cclust_package

cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, Ape-X DQN, DDPG, TD3, SAC)

fixed-point-finder

FixedPointFinder: A Tensorflow toolbox for identifying and characterizing fixed points in recurrent neural networks

gym

A toolkit for developing and comparing reinforcement learning algorithms.

keras-io

Keras documentation, hosted live at keras.io

kimyang2017_cell

multitask

neurogym

A curated collection of neuroscience tasks with a common interface.

pycog

Train excitatory-inhibitory recurrent neural networks for cognitive tasks.

pyrl

recurrent-neural-networks-from-scratch-using-pytorch

LSTM, RNN and GRU implementations using Pytorch

rl-adventure-2

PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay

rl-handson-rlvs21

Stable-Baselines3 (SB3) reinforcement learning tutorial for the Reinforcement Learning Virtual School 2021.

rl-tutorial-jnrr19

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

spinningup

An educational resource to help anyone learn deep reinforcement learning.

stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

temporalskip

wong-wang-2006

Model for perceptual-decision making and working memory from Wong and Wang, J. Neuroscience, 2006