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.

caml-tc

A carbon-aware ML training scheduling system that optimises machine learning workloads using real-time UK grid carbon intensity data. It simulates ML training, finds optimal low-carbon execution windows, and visualises carbon savings through an interactive multi-page Streamlit analytics dashboard.

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.

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.

grid-royale

A framework for multi-agent reinforcement learning.

pydbm

`pydbm` is Python library for building Restricted Boltzmann Machine(RBM), Deep Boltzmann Machine(DBM), Long Short-Term Memory Recurrent Temporal Restricted Boltzmann Machine(LSTM-RTRBM), and Shape Boltzmann Machine(Shape-BM). From the view points of functionally equivalents and structural expansions, this library also prototypes many variants such as Encoder/Decoder based on LSTM, Convolutional Auto-Encoder, and Spatio-temporal Auto-Encoder.

pygan

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.

reinforcement-learning-keras

Reinforcement learning algorithms implemented in Keras (tensorflow==2.3) and sklearn

deer

DEEp Reinforcement learning framework

research

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

marley

A framework for multi-agent reinforcement learning.

pycomposer

pycomposer is Python library for Algorithmic Composition or Automatic Composition based on the stochastic music theory and the Statistical machine learning problems. Especialy, this library provides apprication of the Algorithmic Composer based on Generative Adversarial Networks(GANs) and Conditional Generative Adversarial Networks(Conditional GANs).

qubot

🤖 Autonomous software acceptance testing library for Python taken from my Qubot paper.

quatrix

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

fingym

A tool for developing reinforcement learning algorithms focused in stock prediction

deepcubeai

Learning Discrete World Models for Heuristic Search

simple-q

Low learning-curve implementation of standard Q-learning.

easymyai

Библиотека для создания ИИ, написана ПОЛНОСТЬЮ с нуля

rocketgym

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

literature

Literature card game implementation

lycorisq

A neat reinforcement learning framework based on LycorisNet.

lrl

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