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Artificial Intelligence code snippet how to implement a Learner class that has to optimize its reward from an N-armed bandit. As one would expect, the Learner class knows nothing about the N-Armed Bandit class' internals.
Give a Learner a set of actions, with every action having a certain expected reward. Actions taken are evaluated by adjusting the expected rewards. The chance an action is equal to its expected reward of the sum of expected rewards.
The Learner class has an internal Strategy Design Pattern, which enables the user to select a different Learning Strategy at run-time. In the example main, this Strategy is set randomly.
* Download the 'NarmedBanditLearner' source code (zip)
* Download the 'NarmedBanditLearner' source code (rar)
* Download the 'NarmedBanditLearner' Windows executable (zip)
* Download the 'NarmedBanditLearner' Windows executable (rar)
NarmedBanditLearner, an N-armed bandit and learner class demonstration
Copyright (C) 2006 Richel Bilderbeek
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
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Go back to Richel Bilderbeek's C++ page.
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