Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Finite-State Approximations to Discounted and Average Cost Constrained
  Markov Decision Processes   In this paper, we consider the finite-state approximation of a discrete-time
constrained Markov decision process (MDP) under the discounted and average cost
criteria. Using the linear programming formulation of the constrained
discounted cost problem, we prove the asymptotic convergence of the optimal
value of the finite-state model to the optimal value of the original model.
With further continuity condition on the transition probability, we also
establish a method to compute approximately optimal policies. For the average
cost, instead of using the finite-state linear programming approximation
method, we use the original problem definition to establish the finite-state
asymptotic approximation of the constrained problem and compute approximately
optimal policies. Under Lipschitz type regularity conditions on the components
of the MDP, we also obtain explicit rate of convergence bounds quantifying how
the approximation improves as the size of the approximating finite state space
increases.

6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
19
The categories of this paper are: eess
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con