TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
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Updated
Jul 8, 2024 - Python
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Python implementations of contextual bandits algorithms
Open Bandit Pipeline: a python library for bandit algorithms and off-policy evaluation
[IJAIT 2021] MABWiser: Contextual Multi-Armed Bandits Library
Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)
👤 Multi-Armed Bandit Algorithms Library (MAB) 👮
A lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.
🐈⬛ Contextual bandits library for continuous action trees with smoothing in JAX
Blocks World -- Simulator, Code, and Models (Misra et al. EMNLP 2017)
Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"
Contextual Multi-Armed Bandit Platform for Scoring, Ranking & Decisions
Business Process Improvement with Reinforcement Learning and Human-in-the-Loop.
Contextual multi-armed bandit recommender system using Vowpal Wabbit
Contextual Multi-Armed Bandit Reward Tracker & Model Trainer
This repository aims at learning most popular MAB and CMAB algorithms and watch how they run. It is interesting for those wishing to start learning these topics.
Code for our PRICAI 2022 paper: "Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior".
Bandits codes contributed by Louie Hoang at MSR.
Code of the NeuralBandit paper
WIP: A library and AWS sdk for non-contextual and contextual Multi-Armed-Bandit (MAB) algorithms for multiple use cases
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