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The multi-armed bandit problem is named by analogy to the one-armed bandit machine. In the multi-arms case, the gambler has to decide which arm to pull in order to maximize his total reward in a series of trials.

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Bandit library

Several bandit strategies have been compiled in a .Net library written in C#. Please have a look at the documentation for the list of implemented strategies. Version 0.2 is restricted to the stochastic multi-armed bandit problem, where the underlying reward distributions for each lever do not change over time. The library is provided under LGPL open source licence.

Datasets

The following provided datasets could be used to benchmark the various bandit strategies.

Publications

Links

Author: Joannès Vermorel
Last updated: Tuesday, 24 January, 2006