Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stochastic Constraint Programming as Reinforcement Learning   Stochastic Constraint Programming (SCP) is an extension of Constraint
Programming (CP) used for modelling and solving problems involving constraints
and uncertainty. SCP inherits excellent modelling abilities and filtering
algorithms from CP, but so far it has not been applied to large problems.
Reinforcement Learning (RL) extends Dynamic Programming to large stochastic
problems, but is problem-specific and has no generic solvers. We propose a
hybrid combining the scalability of RL with the modelling and constraint
filtering methods of CP. We implement a prototype in a CP system and
demonstrate its usefulness on SCP problems.

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The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
16
The categories of this paper are: stat