human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "are parametric markov chains monotonic"):
  Abstract: This paper presents a simple algorithm to check whether reachability probabilities in parametric Markov chains are monotonic in (some of) the parameters. The idea is to construct - only using the graph structure of the Markov chain and local transition probabilities - a pre-order on the states. Our algorithm cheaply checks a sufficient condition for monotonicity. Experiments show that monotonicity in several benchmarks is automatically detected, and monotonicity can speed up parameter synthesis up to orders of magnitude faster than a symbolic baseline.

Includes members:
  Member "on the complexity of reachability in parametric markov decision processes":
    also connected through other hyperedges:
      (none)
  Member "accelerated model checking of parametric markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "symblicit exploration and elimination for probabilistic model checking")
  Member "parametric markov chains pctl complexity and fraction free gaussian elimination":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parameter synthesis for markov models")
  Member "reachability in augmented interval markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parameter synthesis for markov models")
  Member "a storm is coming a modern probabilistic model checker":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the probabilistic model checker storm")
  Member "the complexity of graph based reductions for reachability in markov decision processes":
    also connected through other hyperedges:
      (none)
  Member "parameter synthesis for markov models faster than ever":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the probabilistic model checker storm")
  Member "accelerating parametric probabilistic verification":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "parameter synthesis for markov models")

Question: Please tell me which class the source paper 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)