Bandit Algorithms for Website Optimization by John Myles White

Author:John Myles White [White, John Myles]
Language: eng
Format: epub, pdf
ISBN: 9781449341336
Publisher: O’Reilly Media, Inc.
Published: 2013-06-11T16:00:00+00:00

Exercises

In order to really build a feel for the epsilon-Greedy algorithm, you need to see how it behaves under a variety of circumstances. To do that, you should try out the following exercises:

Use a different number of arms than the five arms we’ve been working with. See how epsilon-Greedy behaves if there are 2 arms and then see how it behaves if there are 200 arms.

Change the probabilities of reward from the Bernoulli arms. How does epsilon-Greedy behave if all of the probabilities are close to 0.0? How does it behave it all of the probabilities are close to 1.0? How does it behave when the probabilities for different arms are similar? How does it behave when they’re far apart?

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