Q Learning Python Packages

q-transformer

Implementation of Q-Transformer, Scalable Offline Reinforcement Learning via Autoregressive Q-Functions, out of Google Deepmind

accelbrainbeat

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

pysummarization

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

quatrix

Q-Compass architecture — RL-grounded sequence mixing for text, vision, audio, world modeling, and cross-field tasks

pydbm

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

accel-brain-base

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

pyqlearning

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

pygan

pygan is Python library to implement Generative Adversarial Networks(GANs), Conditional GANs, Adversarial Auto-Encoders(AAEs), and Energy-based Generative Adversarial Network(EBGAN).

grid-royale

A framework for multi-agent reinforcement learning.

research

A collection of machine learning and reinforcement learning algorithms for my PhD research and/or personal education.

deer

DEEp Reinforcement learning framework

reinforcement-learning-keras

No description available

simple-q

Low learning-curve implementation of standard Q-learning.

qubot

Qubot automated testing framework.

pycomposer

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

marley

A framework for multi-agent reinforcement learning.

literature

Literature card game implementation: https://en.wikipedia.org/wiki/Literature_(card_game)

rocketgym

Custom OpenAI Gym for vertical rocket landing and Deep Q-Learning implementation.

lycorisq

A neat reinforcement learning framework based on LycorisNet.

deepcubeai

Learning Discrete World Models for Heuristic Search

fingym

A tool for developing reinforcement learning algorithms focused in stock prediction

easymyai

Easy creation of your own simple neural network

lrl

lrl: Learn Reinforcement Learning - A package to help people learn basic planning and Reinforcement Learning

tabular-rl

A simple Reinforcement Learning framework to decouple agents from environments in discrete-state settings with implementations of double Q-learning and policy iteration through dynamic programming.