Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Reduction-Based Framework for Conservative Bandits and Reinforcement
  Learning   In this paper, we present a reduction-based framework for conservative
bandits and RL, in which our core technique is to calculate the necessary and
sufficient budget obtained from running the baseline policy. For lower bounds,
we improve the existing lower bound for conservative multi-armed bandits and
obtain new lower bounds for conservative linear bandits, tabular RL and
low-rank MDP, through a black-box reduction that turns a certain lower bound in
the nonconservative setting into a new lower bound in the conservative setting.
For upper bounds, in multi-armed bandits, linear bandits and tabular RL, our
new upper bounds tighten or match existing ones with significantly simpler
analyses. We also obtain a new upper bound for conservative low-rank MDP.

25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int