Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Max $K$-Armed Bandit: A PAC Lower Bound and tighter Algorithms   We consider the Max $K$-Armed Bandit problem, where a learning agent is faced
with several sources (arms) of items (rewards), and interested in finding the
best item overall. At each time step the agent chooses an arm, and obtains a
random real valued reward. The rewards of each arm are assumed to be i.i.d.,
with an unknown probability distribution that generally differs among the arms.
Under the PAC framework, we provide lower bounds on the sample complexity of
any $(\epsilon,\delta)$-correct algorithm, and propose algorithms that attain
this bound up to logarithmic factors. We compare the performance of this
multi-arm algorithms to the variant in which the arms are not distinguishable
by the agent and are chosen randomly at each stage. Interestingly, when the
maximal rewards of the arms happen to be similar, the latter approach may
provide better performance.

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The categories of this paper are: nucl-ex
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The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
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The categories of this paper are: hep-ph
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The categories of this paper are: math-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: ao-sci