In this article, I will explore the balance between exploration and exploitation, a key concept in reinforcement learning and optimization problems. To illustrate this, I will use the multi-armed bandit problem as an example. I will also explain how the epsilon-greedy strategy effectively manages this balance.

I- Introduction

In a previous article, I introduced the design and implementation of a multi-armed bandit (MAB) framework. This framework was built to simplify the implementation of new MAB strategies and provide a structured approach for their analysis.

In previous blog posts, we explored the multi-armed bandit (MAB) problem and discussed the Upper Confidence Bound (UCB) algorithm as one approach to solving it. Research literature has introduced multiple algorithms for tackling this problem, and there is always room for experimenting with new ideas. To facilitate the implementation and comparison of different algorithms, we introduce a framework for MAB solvers.

This article focuses on evaluating the implementation of the Upper Confidence Bound (UCB) algorithm discussed herein. The evaluation is conducted using a single dataset provided by Super Data Science.

This article explores the implementation of a reinforcement learning algorithm called the Upper Confidence Bound (UCB) algorithm. Reinforcement learning, a subset of artificial intelligence, involves an agent interacting with an environment through a series of episodes or rounds. In each round, the agent makes a decision that may yield a reward. The agent's ultimate objective is to learn a strategy that maximizes its cumulative reward over time.

I have purchased, last weekend, Paul Hoffman's book The Man Who Only Loved Numbers. This is a biography of the great and equally eccentric number theorist of all times Paul Érdös.

The book has been published in 1998, two years after the death of Érdös in Warsaw. The first 25% of Hoffman's book is interesting and entertaining at the same time. It tell the story of a man who devoted his whole life to Mathematics, who travelled from country to country carrying all his belongings in a briefcase and a bag.

Je viens d'acquérir une SlingBox. La SlingBox est un équipement que l'on connecte à un terminal de réception télé et à un routeur. La SlingBox permet par la suite de contrôler ce terminal télé à distance là où une connexion Internet est disponible et aussi d'écouter la télé à l'autre bout du monde comme si on était chez soi. La SlingBox vient en deux moèles la SlingBox 350, à 179$, et la SlingBox 500 à 299$. Le dernier modèle dispose d'une connexion sans fil et d'un port HDMI.