Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Model-Based Reinforcement Learning Framework of Online Network Resource
  Allocation   Online Network Resource Allocation (ONRA) for service provisioning is a
fundamental problem in communication networks. As a sequential decision-making
under uncertainty problem, it is promising to approach ONRA via Reinforcement
Learning (RL). But, RL solutions suffer from the sample complexity issue; i.e.,
a large number of interactions with the environment needed to find an efficient
policy. This is a barrier to utilize RL for ONRA as on one hand, it is not
practical to train the RL agent offline due to lack of information about future
requests, and on the other hand, online training in the real network leads to
significant performance loss because of the sub-optimal policy during the
prolonged learning time. This performance degradation is even higher in
non-stationary ONRA where the agent should continually adapt the policy with
the changes in service requests. To deal with this issue, we develop a general
resource allocation framework, named RADAR, using model-based RL for a class of
ONRA problems with the known immediate reward of each action. RADAR improves
sample efficiency via exploring the state space in the background and
exploiting the policy in the decision-time using synthetic samples by the model
of the environment, which is trained by real interactions. Applying RADAR on
the multi-domain service federation problem, to maximize profit via selecting
proper domains for service requests deployment, shows its continual learning
capability and up to 44% performance improvement w.r.t. the standard model-free
RL solution.

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The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph