🌾 OAT: A research-friendly framework for LLM online alignment, including reinforcement learning, preference learning, etc.

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

👤 Multi-Armed Bandit Algorithms Library (MAB) 👮

This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).

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

Thompson Sampling Tutorial

Python library for Multi-Armed Bandits

All codes, both created and optimized for best results from the SuperDataScience Course

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

Bandit algorithms

Stop overpaying to run your agents. Kalibr routes every request to lower-cost model and tool paths without degrading performance.

pyrff: Python implementation of random fourier feature approximations for gaussian processes

Study of the paper 'Neural Thompson Sampling' published in October 2020

Offline evaluation of multi-armed bandit algorithms

Bayesian Optimization for Categorical and Continuous Inputs

A Julia Package for providing Multi Armed Bandit Experiments

The official code release for "Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning", ICLR 2025

A curated list on papers about combinatorial multi-armed bandit problems.

Self-improving agent governance: 👍/👎 → Pre-Action Checks that block repeat AI mistakes. Stop paying for the same mistake twice.

Implementations of basic concepts dealt under the Reinforcement Learning umbrella. This project is collection of assignments in CS747: Foundations of Intelligent and Learning Agents (Autumn 2017) at IIT Bombay