implement basic and contextual MAB algorithms for recommendation system

The easiest way to optimize Facebook Ads using Upper Confidence Bound Algorithm. 💻

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

Python implementation of UCB, EXP3 and Epsilon greedy algorithms

UCThello - a board game demonstrator (Othello variant) with computer AI using Monte Carlo Tree Search (MCTS) with UCB (Upper Confidence Bounds) applied to trees (UCT in short)

Oware and Ouril - traditional African Mancala games with computer AI using Monte Carlo Tree Search (MCTS) with UCB (Upper Confidence Bounds) applied to trees (UCT in short)

Implementation of greedy, E-greedy and Upper Confidence Bound (UCB) algorithm on the Multi-Armed-Bandit problem.

The example of using reinforcement learning algorithms in the business, specifically finding what ads to use in our campaign.

3 dimensional Four in a Row game with computer AI using Monte Carlo Tree Search (MCTS) with UCB (Upper Confidence Bounds) applied to trees (UCT in short).

Alquerque - a 2 player abstract strategic perfect information traditional board game with computer AI option.

AI for the game "Connect Four". Available on PyPI.

A simple implementation of Reinforcement Learning using UCB in python.

A Comparative Evaluation of Active Learning Methods in Deep Recommendation

This repository inclues the Samurai framework and all the implemented base engines.

A python based ML tool for CRT inspection & optimization

An AI agent implemented using Monte Carlo Tree Search (MCTS) using Upper Confidence Bounds (UCT).

A fighting game AI: KeepAwayBot, implemented in Java using Hierarchical Task Networks and the Upper Confidence Bounds Algorithm

Tools for implementing upper confidence bound optimization