human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "range and roots two common patterns for specifying and propagating counting and occurrence constraints"
  Abstract: We propose Range and Roots which are two common patterns useful for specifying a wide range of counting and occurrence constraints. We design specialised propagation algorithms for these two patterns. Counting and occurrence constraints specified using these patterns thus directly inherit a propagation algorithm. To illustrate the capabilities of the Range and Roots constraints, we specify a number of global constraints taken from the literature. Preliminary experiments demonstrate that propagating counting and occurrence constraints using these two patterns leads to a small loss in performance when compared to specialised global constraints and is competitive with alternative decompositions using elementary constraints.

Connected through hyperedge HE-1 (induced by source paper "conjunctions of among constraints"):
  with members:
    - "propagating conjunctions of alldifferent constraints"
    - "slide a useful special case of the cardpath constraint"
    - "flow based propagators for the sequence and related global constraints"

Connected through hyperedge HE-2 (induced by source paper "guarantees and limits of preprocessing in constraint satisfaction and reasoning"):
  with members:
    - "on feedback vertex set new measure and new structures"
    - "parameterized complexity and kernel bounds for hard planning problems"
    - "backdoors to satisfaction"
    - "backdoors to tractable answer set programming"
    - "limits of preprocessing"
    - "kernels for global constraints"
    - "the parameterized complexity of global constraints"
    - "cutset sampling for bayesian networks"

Connected through hyperedge HE-3 (induced by source paper "limits of preprocessing"):
  with members:
    - "backdoors to tractable answer set programming"
    - "kernels for global constraints"
    - "the parameterized complexity of global constraints"
    - "kernel s for problems with no kernel on out trees with many leaves"
    - "cutset sampling for bayesian networks"
    - "stable models and an alternative logic programming paradigm"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.AI(Artificial Intelligence)