Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Acceleration Operators in the Value Iteration Algorithms for Average
  Reward Markov Decision Processes   One of the most widely used methods for solving average cost MDP problems is
the value iteration method. This method, however, is often computationally
impractical and restricted in size of solvable MDP problems. We propose
acceleration operators that improve the performance of the value iteration for
average reward MDP models. These operators are based on two important
properties of Markovian operator: contraction mapping and monotonicity. It is
well known that the classical relative value iteration methods for average cost
criteria MDP do not involve the max-norm contraction or monotonicity property.
To overcome this difficulty we propose to combine acceleration operators with
variants of value iteration for stochastic shortest path problems associated
average reward problems.

15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th