Linearly parameterized bandits
We consider bandit problems involving a large (possibly infinite) collection of arms, in which the expected reward of each arm is a linear function of an r-dimensional random vector Z ∈ ℝ(superscript r), where r ≥ 2. The objective is to minimize the cumulative regret and Bayes risk. When the set of...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
INFORMS,
2012-06-04T18:10:35Z.
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| Subjects: | |
| Online Access: | Get fulltext |