Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Online Markov decision processes with policy iteration   The online Markov decision process (MDP) is a generalization of the classical
Markov decision process that incorporates changing reward functions. In this
paper, we propose practical online MDP algorithms with policy iteration and
theoretically establish a sublinear regret bound. A notable advantage of the
proposed algorithm is that it can be easily combined with function
approximation, and thus large and possibly continuous state spaces can be
efficiently handled. Through experiments, we demonstrate the usefulness of the
proposed algorithm.

3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
22
The categories of this paper are: chao-dyn