Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Q-learning with censored data   We develop methodology for a multistage decision problem with flexible number
of stages in which the rewards are survival times that are subject to
censoring. We present a novel Q-learning algorithm that is adjusted for
censored data and allows a flexible number of stages. We provide finite sample
bounds on the generalization error of the policy learned by the algorithm, and
show that when the optimal Q-function belongs to the approximation space, the
expected survival time for policies obtained by the algorithm converges to that
of the optimal policy. We simulate a multistage clinical trial with flexible
number of stages and apply the proposed censored-Q-learning algorithm to find
individualized treatment regimens. The methodology presented in this paper has
implications in the design of personalized medicine trials in cancer and in
other life-threatening diseases.

28
The categories of this paper are: alg-geom
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
1
The categories of this paper are: cs
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat