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Results tagged with multi-armed-bandits
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For questions related to the multi-armed bandit (MAB) problem, in which a fixed limited set of resources must be allocated between competing (alternative) choices in a way that maximizes their expected gain, when each choice's properties are only partially known at the time of allocation.
7
votes
Accepted
Are bandits considered an RL approach?
Several important researchers distinguish between bandit problems and the general reinforcement learning problem.
The book Reinforcement learning: an introduction by Sutton and Barto describes bandit …
- 41.4k
4
votes
Accepted
Why aren't exploration techniques, such as UCB or Thompson sampling, used in full RL problems?
You can indeed use UCB in the RL setting. See e.g. section 38.5 Upper Confidence Bounds for Reinforcement Learning (page 521) of the book Bandit Algorithms by Csaba Szepesvari and Tor Lattimore for th …
- 41.4k