upper-confidence-bounds

farhanchoudhary/Machine_Learning_A-Z_All_Codes_and_Templates

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

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

implement basic and contextual MAB algorithms for recommendation system

kulinshah98/Multi-Armed-Bandit-Algorithms

Python implementation of UCB, EXP3 and Epsilon greedy algorithms

OMerkel/UCThello

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)

atse0612/Machine-Learning-A-Z

OMerkel/Oware

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)

KaleabTessera/Multi-Armed-Bandit

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

lucko515/ads-strategy-reinforcement-learning

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

OMerkel/Alquerque

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

OMerkel/FourInARow3D

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).

woctezuma/puissance4

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

mahesh147/Upper-Confidence-Bound

A simple implementation of Reinforcement Learning using UCB in python.

joansalasoler/engines

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

k9luo/Deep-Preference-Elicitation

A Comparative Evaluation of Active Learning Methods in Deep Recommendation

uditkumar489/Marketing-Campaign-Analyser

A python based ML tool for CRT inspection & optimization

chaitanya100100/AI-Agent-for-Ultimate-Tic-Tac-Toe

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

BryanRam/HTNResearch

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

FaydSpeare/Checkers

Strong Aritifical Intelligence for Checkers created using Upper Confidence Tree algorithm with GUI.

jonathan-greenhalgh/UCB_optimization

Tools for implementing upper confidence bound optimization

naman-dhammi/Ads_Optimisation

(REINFORCEMENT LEARNING) : We are given a dataset that contains information about the ads clicked by the visitors at each visit to a webpage (amongst 10 different ads). Our Task is to find the most viewed ad i.e ad having the highest distribution of the viewers in Minimum number of Rounds and Resources. Here I have used "Upper Confidence Bound" and "Thompson Sampling" models to get the insights.

PRAN20/Upper-Confidence-Bound

Eric-Su-2718/Reinforcement-learning-methods-for-the-multi-armed-bandit-problem

Implementation of the Upper confidence bounds and Thompson sampling algorithms in R for the multi armed bandit problem

FaydSpeare/3D_Connect_4

Strong Artificial Intelligence for 3-Dimensional Connect 4 using Upper Confidence Tree Algorithm

hughyi/Research-Project

Advised by Prof. Jungmin So - spring '23

intmod/gobang

A very simple yet serious gobang game AI based on Monte-Carlo Tree Search and implemented in pure Python

kulinshah98/AI-Agent-Tic-Tac-Toe

A python implementation of an agent for ultimate tic-tac-toe using Monte Carlo Tree Search and Upper Confidential Bound

ml-repos/MachineLearning-Projects-2

Real-Life Example for Machine Learning Projects (Python3) -Part-2

zec37/mcts_practice

A simple simulation of mcts tree search

dixitamol/ML_code_templates_R

Code templates for different ML algorithms

doguilmak/Random-Seleciton-Upper-Confidence-Bound-and-Thompson-Sampling-on-Advertising-Preference

The purpose of this study is to predict which ad will be the most preferred by the customers over the fictitious ads clicked by the users.

krishnaaxo/Reinforcement-UCB-ThompsonSampling

Sanket758/Machine-Learning-A-Z

singhgaurav2323/reinforcement

Reinforcement learning