PDF4PRO ⚡AMP

Modern search engine that looking for books and documents around the web

Example: air traffic controller

ATutorialonThompsonSampling - Stanford University

Back to document page

A Tutorial on Thompson SamplingDaniel J. Russo1, Benjamin Van Roy2, Abbas Kazerouni2, IanOsband3and Zheng Wen41Columbia University2Stanford University3Google DeepMind4Adobe ResearchABSTRACTThompson sampling is an algorithm for online decision prob-lems where actions are taken sequentially in a manner thatmust balance between exploiting what is known to maxi-mize immediate performance and investing to accumulatenew information that may improve future performance. Thealgorithm addresses a broad range of problems in a compu-tationally efficient manner and is therefore enjoying wideuse. This tutorial covers the algorithm and its application,illustrating concepts through a range of examples, includingBernoulli bandit problems, shortest path problems, productrecommendation, assortment, active learning with neuralnetworks, and reinforcement learning in Markov decisionprocesses.

TS, specialized to the case of a beta-Bernoulli bandit, proceeds similarly,aspresentedinAlgorithm2.Theonlydifferenceisthatthe successprobabilityestimate ...

Download ATutorialonThompsonSampling - Stanford University


Information

Domain:

Source:

Link to this page:

Please notify us if you found a problem with this document:

Spam in document Broken preview Other abuse

Related search queries