Multi-Armed Bandit Analysis for Price Optimization

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Lately, I have read a blog post titled Bandits Know the Best Product Price"
(<a href="http://pkghosh.wordpress.com/2013/08/25/bandits-know-the-best-product-price/">http://pkghosh.wordpress.com/2013/08/25/bandits-know-the-best-product-price/</a>), which outlines how to use multi-armed bandit analysis for price optimization.

There is also a lot of discussion on whether multi-armed bandit analysis is better than A/B testing (e.g. "20 lines of code that will beat A/B testing every time": <a href="http://stevehanov.ca/blog/index.php?id=132?utm_medium=referral">http://stevehanov.ca/blog/index.php?id=132?utm_medium=referral</a> versus "Why multi-armed bandit algorithm is not 'better' than A/B testing": <a href="http://visualwebsiteoptimizer.com/split-testing-blog/multi-armed-bandit-algorithm/">http://visualwebsiteoptimizer.com/split-testing-blog/multi-armed-bandit-algorithm/</a>).

I am aware that there is a R package called "bandit", which can be used for such an analysis.

Does someone has a <strong>toy example -</strong> comparable to the one in the blog post - which shows how to apply this method by using R (<strong>within the context of price optimization</strong>)?

Thanks for your help.