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multiarmed-bandits

Here are 59 public repositories matching this topic...

david-cortes / contextualbandits

Python implementations of contextual bandits algorithms

reinforcement-learning contextual-bandits multiarmed-bandits exploration-exploitation

Updated Nov 4, 2024
Python

alison-carrera / onn

Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)

reinforcement-learning neural-network pytorch thompson-sampling reinforcement-learning-algorithms machine-learning-library neural-architecture-search contextual-bandits mab pytorch-implemention multiarmed-bandits pytorch-implementation thompson-algorithm

Updated Dec 11, 2019
Python

mab

stitchfix / mab

Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.

go golang data-science reinforcement-learning thompson-sampling experimentation multi-armed-bandits multi-armed-bandit thompson multiarmed-bandits

Updated Dec 7, 2024
Go

Heewon-Hailey / multi-armed-bandits-for-recommendation-systems

implement basic and contextual MAB algorithms for recommendation system

python numpy scikit-learn epsilon-greedy recommendation-system matplotlib upper-confidence-bounds contextual-bandits multiarmed-bandits

Updated Jan 18, 2022
Jupyter Notebook

irec-org / irec

Interactive Recommender Systems Framework

reinforcement-learning recommender-system multiarmed-bandits interactive-recommender

Updated Apr 5, 2024
Python

Bilkent-CYBORG / ACC-UCB

Implementation of the Adaptive Contextual Combinatorial Upper Confidence Bound (ACC-UCB) algorithm for the contextual combinatorial volatile multi-armed bandit setting.

reinforcement-learning contextual-bandit multiarmed-bandits combinatorial-bandit

Updated Feb 24, 2020
Python

ShreenidhiN / Reinforcement-Learning-based-Movie-Recommendation

Recommender Systems are the systems designed to that are designed to recommend things to the user based on many different factors. These systems predict the most likely product that the users are most likely to purchase and are of interest to. Recommendations typically speed up searches and make it easier for users to access content they’re inte…

reinforcement-learning deep-reinforcement-learning multiarmed-bandits actor-critic-model

Updated Jan 3, 2023
Jupyter Notebook

rklymentiev / mab_problem

how to deal with multi-armed bandit problem through different approaches

ab-testing flask-app multiarmed-bandits

Updated Jul 6, 2023
HTML

beer-recommender-mab

paulozip / beer-recommender-mab

A beer recommendation system using multi-armed bandit approach to solve cold start problems

python recommendation-system multi-armed-bandits multiarmed-bandits

Updated Oct 30, 2020
Python

babaniyi / Deep-contextual-bandits

A benchmark to test decision-making algorithms for contextual-bandits. The library implements a variety of algorithms (many of them based on approximate Bayesian Neural Networks and Thompson sampling), and a number of real and syntethic data problems exhibiting a diverse set of properties.

bandits bandit-algorithms multiarmed-bandits

Updated Jan 26, 2022
Python

R4j4n / Maximizing-Revenue-of-an-Online-Retail-Business

thompson-sampling multiarmed-bandits thompson-algorithm revenue-systems

Updated Sep 8, 2020
Python

formidablae / Batched_Multi-armed_Bandits

Batched Multi-armed Bandits Problem - Analisi critica. Artificial Intelligence Course Project on the study and experimental results' analysis of a scientific paper.

data-science numpy matlab pandas artificial-intelligence matplotlib armed-bandit multiarmed-bandits

Updated Jan 29, 2022
Python

GjjvdBurg / ThompsonSampling

Source code for blog post on Thompson Sampling

thompson-sampling multi-armed-bandit bandit-algorithms multiarmed-bandits

Updated Sep 4, 2020
JavaScript

Nath-R / LEAF

Learning, Evaluation and Avoidance of Failure situations (LEAF) is a tool to that prevents failures in robot's task plan by learning from previous experience.

robotics ontology learning-by-doing multiarmed-bandits

Updated Feb 19, 2020
Java

prakHr / Reinforcement-Learning-Book

[Book] :- Andrea Lonza - Reinforcement Learning Algorithms with Python_ Learn, understand, and develop smart algorithms for addressing AI challenges-Packt Publishing (2019)

Updated Jul 3, 2020
Python

irec-org / irec-cmdline

The iRec official command line interface

reinforcement-learning recommender-system multiarmed-bandits

Updated May 17, 2023
Jupyter Notebook

raunakkmr / non-monotonic-resource-utilization-in-the-bandits-with-knapsacks-problem-code

This repository contains code for the paper "Non-monotonic Resource Utilization in the Bandits with Knapsacks Problem".

multiarmed-bandits regret-minimization bandits-with-knapsacks knapsack-constraints

Updated Sep 28, 2022
Python

CavenaghiEmanuele / Multi-armed-bandit

Library on Multi-armed bandit

thompson-sampling multiarm-bandit multiarmed-bandits thompson-algorithm

Updated Jan 30, 2023
Python

Shahul-Rahman / MABSearch-Learning-the-learning-rate

MABSearch: The Bandit Way of Learning the Learning Rate - A Harmony Between Reinforcement Learning and Gradient Descent

python machine-learning reinforcement-learning optimization global-optimization gradient-descent learning-rate multi-armed-bandit global-optimization-algorithms metaheuristics multiarm-bandit multiarmed-bandits global-minimum

Updated Oct 28, 2023
Jupyter Notebook

k9luo / Deep-Preference-Elicitation

A Comparative Evaluation of Active Learning Methods in Deep Recommendation

tensorflow python3 thompson-sampling recommender-system upper-confidence-bounds active-learning activelearning multiarmed-bandits sequential-recommendation

Updated Jul 14, 2019
Jupyter Notebook

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