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: "quantitative computation tree logic model checking based on generalized possibility measures"
  Abstract: We study generalized possibilistic computation tree logic model checking in this paper, which is an extension of possibilistic computation logic model checking introduced by Y.Li, Y.Li and Z.Ma (2014). The system is modeled by generalized possibilistic Kripke structures (GPKS, in short), and the verifying property is specified by a generalized possibilistic computation tree logic (GPoCTL, in short) formula. Based on generalized possibility measures and generalized necessity measures, the method of generalized possibilistic computation tree logic model checking is discussed, and the corresponding algorithm and its complexity are shown in detail. Furthermore, the comparison between PoCTL introduced in (2013) and GPoCTL is given. Finally, a thermostat example is given to illustrate the GPoCTL model-checking method.

Connected through hyperedge HE-1 (induced by source paper "quantitative model checking of linear time properties based on generalized possibility measures"):
  with members:
    - "computation tree logic model checking based on possibility measures"
    - "discounting in ltl"
    - "model checking of linear time properties based on possibility measure"

Connected through hyperedge HE-2 (induced by source paper "fuzzy alternating mathrm b ddot u chi automata over distributive lattices"):
  with members:
    - "quantitative model checking of linear time properties based on generalized possibility measures"
    - "model checking of linear time properties based on possibility measure"

Connected through hyperedge HE-3 (induced by source paper "model checking of linear time properties in multi valued systems"):
  with members:
    - "quantitative model checking of linear time properties based on generalized possibility measures"
    - "computation tree logic model checking based on possibility measures"
    - "model checking of linear time properties based on possibility measure"
    - "model checking for a class of weighted automata"

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.LO(Logic in Computer Science)