Q Learning Python Packages

mdplib

Fast solvers for infinite-horizon discounted Markov Decision Processes (value iteration, Gauss-Seidel VI, policy iteration, Q-learning, SARSA) with a C++/pybind11 backend.

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.

q-transformer

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

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.

research

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

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.

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.

grid-royale

A framework for multi-agent reinforcement learning.

qubot

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

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.

deer

DEEp Reinforcement learning framework

marley

A framework for multi-agent reinforcement learning.

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.

rocketgym

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

simple-q

Low learning-curve implementation of standard Q-learning.

quatrix

Quatrix — Q-Compass Architecture: novel neural architecture replacing attention with value-based navigation. Base for the Quasar model series.

reinforcement-learning-keras

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

mdp-solver-ic

Fast solvers for infinite-horizon discounted Markov Decision Processes (value iteration, Gauss-Seidel VI, policy iteration, Q-learning, SARSA) with a C++/pybind11 backend.

literature

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

easymyai

Библиотека для создания ИИ, написана ПОЛНОСТЬЮ с нуля

fingym

A tool for developing reinforcement learning algorithms focused in stock prediction

lycorisq

A neat reinforcement learning framework based on LycorisNet.