Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reinforcement Learning for Optimal Load Distribution Sequencing in
  Resource-Sharing System   Divisible Load Theory (DLT) is a powerful tool for modeling divisible load
problems in data-intensive systems. This paper studied an optimal divisible
load distribution sequencing problem using a machine learning framework. The
problem is to decide the optimal sequence to distribute divisible load to
processors in order to achieve minimum finishing time. The scheduling is
performed in a resource-sharing system where each physical processor is
virtualized to multiple virtual processors. A reinforcement learning method
called Multi-armed bandit (MAB) is used for our problem. We first provide a
naive solution using the MAB algorithm and then several optimizations are
performed. Various numerical tests are conducted. Our algorithm shows an
increasing performance during the training progress and the global optimum will
be acheived when the sample size is large enough.

26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int