Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Finding the Near Optimal Policy via Adaptive Reduced Regularization in
  MDPs   Regularized MDPs serve as a smooth version of original MDPs. However, biased
optimal policy always exists for regularized MDPs. Instead of making the
coefficient{\lambda}of regularized term sufficiently small, we propose an
adaptive reduction scheme for {\lambda} to approximate optimal policy of the
original MDP. It is shown that the iteration complexity for obtaining
an{\epsilon}-optimal policy could be reduced in comparison with setting
sufficiently small{\lambda}. In addition, there exists strong duality
connection between the reduction method and solving the original MDP directly,
from which we can derive more adaptive reduction method for certain algorithms.

19
The categories of this paper are: eess
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math