Bandit Algorithms

Discover the intricacies of decision-making under uncertainty with Bandit Algorithms by Tor Lattimore, published by Cambridge University Press in 2020. This hardback edition spans an impressive 536 pages, making it an essential resource for both seasoned researchers and graduate students alike.

Delve into the widely-used multi-armed bandit model, a key framework in machine learning, designed to tackle the challenges of uncertainty. This comprehensive introduction covers a variety of approaches, including stochastic, adversarial, and Bayesian frameworks, providing valuable insights for those looking to deepen their understanding of the field. Whether you are advancing your research or starting your academic journey, Bandit Algorithms is the perfect guide to navigate the complexities of decision-making in machine learning.