Bayesian active learning algorithm with Thompson sampling on multi-armed bandit with Numpy

Assignments for CS747 - Foundations of Intelligent and Learning Agents

A multi-armed bandit implementation in python

Implementation of multi-armed bandits from scratch

unRL (AKA "unreal") is a set of libraries providing Reinforcement Learning algorithms implemented in PyTorch or Jax.

Development of algorithms for reinforcement learning. Specifically, software implementation of the algorithms and policies described in the paper Batched Multi-armed Bandits Problems, by Zijun Gao, Yanjun Han, Zhimei Ren, Zhengqing Zhou.

FlicksMAB is a movie recommendation system that leverages the power of multi-armed bandits (MAB) to personalize movie suggestions for users. Built using PyTorch, this system uses the MovieLens 100K dataset to learn user preferences and recommend movies that are likely to engage them.

Multi Armed Bandits implementation using the Jester Dataset

A repository covering a range of topics from multi-arm bandits to reinforcement learning algorithms. Check out different applications of bandits, MDPs and RL algorithms along with theoretical aspects.

Package to implement the Thompson Sampling algorithm.

Implementation of the prophet inequalities

Contextual Bandit Engine

IEEE 802.11bn Multi-AP Coordinated Spatial Reuse with Hierarchical Multi-Armed Bandits

This repository addresses popular content recommender design for public transportation as discussed in my Ph.D. thesis titled as: "Popular Content Distribution in Public Transportation Using Artificial Intelligence Techniques". The code used for the entire content recommender design is provided twice using two programming languages, namely: Pyth…

Code for Policy Optimization as Online Learning with Mediator Feedback

Repository for the course project done as part of CS-747 (Foundations of Intelligent & Learning Agents) course at IIT Bombay in Autumn 2022.

An implementation of Bayesian AB testing framework in Django. Implements multi-armed bandit algorithms such as Thompson Sampling and UCB1. API for registering impressions/conversions implemented with django-rest framework

WIP: A library and AWS sdk for non-contextual and contextual Multi-Armed-Bandit (MAB) algorithms for multiple use cases

Implementation of several multi-armed bandit problems.

This project provides a simulation of multi-armed bandit problems. This implementation is based on the below paper. https://arxiv.org/abs/2308.14350.